Schedule 2018

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  • Day 1

    Sep 26, 2018

  • 09:15 - 10:00
    India is fast emerging as an AI hotbed, thanks to its strong talent base, government support, a burgeoning start-up ecosystem, rising VC interest and plethora of innovation across various sectors. But is the adoption of Artificial Intelligence in India as rapid as its global counterparts like China, Japan, Singapore, Germany, UK and US? Through this session, the speaker presents his take on the current landscape of AI in India and its adoption compared to other countries leading in this space. His talk will also touch upon some of the areas where AI could drive a new frontier of futuristic opportunities in India, and what will it take for India to emerge as a leader on the Global AI stage.
    Hall 1: Keynotes & Panels

  • 10:00 - 11:00
    It will touch every corner of society. From using image recognition to enhance public security, to giving automated services a human touch with natural language processing, Intel® Xeon® processors are the foundation of today’s AI and tomorrow’s transformation. Intel has the industry’s most comprehensive suite of hardware and software technologies that deliver broad capabilities and support diverse approaches for AI—including today’s AI applications and more complex AI tasks in the future.
    Hall 4: Workshops

  • 10:00 - 10:35
    Though a lot has been talked about the emerging technologies, there are still a lot of unknowns on the concepts. SAP has taken a differentiated modular approach to emerging technologies to help its clients. To bring it to life, Shailendra will take a use case approach to showcase how large organisations are becoming “Intelligent Enterprise” to Make Money out of Data.
    Hall 1: Keynotes & Panels

  • 10:00 - 13:00
    Our everyday life is dominated by powerhouses of Artificial Intelligence and Deep Learning that started off small and grew big in different domains across industries like financial services, insurance, HR, retail, e-commerce, healthcare, news publishing, transportation, food delivery etc. In this master class, we will discuss how deep learning & AI revolutionizes chat-bots, addressing some of the limitations of NLP and demystifying the chat-bots. A chatbot can be anything from a simple service giving you a local weather forecast, to a complex enterprise-grade integrated IT solution. With advancements in Artificial Intelligence, deep learning techniques and Natural Language Processing, Chat-bots are revolutionizing the Service Industry. Uber, NBA, TacoBell, CNN, H&M, Nike, Quartz, Unicef, Barbie, Citi Bank etc are some of the 1500+ large corporations which are already using chatbots.
    Hall 3: Masterclass & Talks

  • 10:00 - 10:35
    Insurance has been the earliest adopter of data but the latest one of data Analytics. Historically, Insurers have collected wealth of data, but have been really slow in using it to its full potential. The optimum usage of that data-wealth along with the external information available about the individuals when assisted with advanced analytical techniques will create wonders for Insurance carriers. With more number of consumers moving to online medium for purchases and interactions, the volume of individual data is increasing exponentially. Artificial intelligence (AI) along with the wave of advanced analytics techniques has the potential to shift “Detect and Repair” approach to “Predict and Prevent” approach.
    Hall 2: Knowledge Talks

  • 10:35 - 11:20
    Hall 1: Keynotes & Panels

  • 10:35 - 11:10
    Every year over 1.3M people die on roads. In recent years the fatality and collisions rates have only gone up, reversing a several decade long downward trend. So even while cars are becoming safer, this recent increase is largely attributed to distraction caused by use of mobile phones while driving. Zendrive, a company committed to making roads safer, is using the same smartphone data to understand unsafe driving behaviors like aggression, adherence to rules of the road and distraction. Using sophisticated machine learning techniques and massive amount of data (150B miles of data over 50M users) Zendrive has built world’s leading driving behavior analysis platform that has already helped save hundreds of lives. This data and analysis also find wide variety of usage in insurance, city planning and driver coaching. In his talk Pankaj Risbood, Co-Founder and VP Data, Engineering at Zendrive will take you on a fascinating journey of measuring driving behavior, quantifying risk and creating incentives for drivers to adopt safer driving habits.
    Hall 2: Knowledge Talks

  • 11:20 - 12:20
    In this workshop we are going to build 3 Cognitive Apps, 1)A Visual Recognition app to analyze image stream and trigger an IoT Device based on certain events2)Build a live transcription cloud app for transcribing speech into text and 3)a text to speech conversion app and finally integrate all the three to IoT Platform building a cognitive Central IoT System
    Hall 4: Workshops

  • 11:30 - 12:05
    Software industry has evolved for more than 40 years now. However, Analytics has still been a big buzz word in the industry. We have learnt an excellent way of choosing software development methodology and executing best possible way to get success in software development. Today, we have waterfall and Agile as popular methodologies for developing software. However, we have failed to understand that Analytics is fundamentally different from Software Development. Analytics Project Development calls completely different execution methodology, we cannot adopt regular SDLC. The discussion is all about, how can you arrive at a best execution methodology that works for you, to bring success.
    Hall 1: Keynotes & Panels

  • 11:30 - 12:05
    Supervised Learning envisages a clear demarcation between the dependent variable and a host of independent variables and provides opportunities to do analytics that predicts the dependent variable based on the independent variables. In the Unsupervised Learning, we have only data and the outcome has to be discovered in terms of pattern emanating from the data. In today’s environment, often times we have to start with Unsupervised Learning, identify pattern, and then move to Supervised Learning for Predictive Analytics involving Classification. Thus the analytics exercise seems to be a journey from Unsupervised to Supervised Learning. A case study that has the primary goal to identify pattern in terms of attitude and behavior of respondents toward IOT is used as a basis to illustrate the power of analytics that travels from Unsupervised to Supervised Learning. Unsupervised Learning involving Hierarchical Clustering was done using Ward’s Procedure. Three clusters were identified-those who will adopt IOT, those who are undecided, and those who will not adopt IOT. The Clusters have been confirmed by way of differentiation and classification using Fisher’s Discriminant Analysis that is a supervised learning procedure. Jack-Knife Method of cross validation has been done to test the veracity of the model. The insights are not only intriguing but also extremely important in establishing the premise that in “Today’s Environment, the Journey is from Unsupervised to Supervised Machine Learning”.
    Hall 2: Knowledge Talks

  • 12:05 - 12:40
    Customer centricity is a core business priority across industries today. The innumerable channels to reach the customer and associated data sources do complicate the problem, but also present a great opportunity to leverage Artificial Intelligence (AI) to drive significant business impact. The discussion will focus on how to drive a new customer marketing paradigm called Next Best Action. Deep learning algorithms combined with evolutionary genetic algorithms form the core of AI and help with recommendations to optimize every touchpoint with the right channel and content for each customer at the right time. Walk in to hear our experience on this exciting topic.
    Hall 2: Knowledge Talks

  • 12:05 - 12:40
    Marketers know they need to put their CRM initiatives on steroids by going hyper personalized, automated, and driven by AI and ML. This session focuses on the Analytics that makes such initiatives work. What algorithm and infrastructure choices can speed up SOO initiatives, where AI can and can’t be applied, how ROI may be measured, and how top management buy-in is achieved.
    Hall 1: Keynotes & Panels

  • 12:40 - 13:15
    Weather affects every inhabitant of Earth, every day, as well as every business that serves them. It impacts everything from energy prices to media consumption, aviation safety to food costs, and so much more. 25% of all home insurance claims are due to exterior wind damage. Demand for gas/petrol/diesel goes up by 31% during extreme weather. Over 90% of all crop losses are due to weather. Moderate changes in weather can drive significant changes in energy prices. Most businesses don't have a weather strategy. In our recent survey of 3000 CEOs, 93% shared that weather affects business. The Weather Company, an IBM Business helps you incorporate weather with 'Cleaned Historical Weather data' for all ML and AI models. Predictive Analytics is a business game changer and predictions based on weather can transform how businesses understand its impact on their operations, anticipate weather events sooner and take action to optimize those parts of their enterprise that might be impacted by weather. Does weather impact your business? What actions should you take based on weather? Join us to hear how we decode weather to help you make informed decisions and achieve the best outcomes.
    Hall 1: Keynotes & Panels

  • 13:30 - 14:30
    Though a lot has been talked about the emerging technologies, there are still a lot of unknowns on the concepts. SAP has taken a differentiated modular approach to emerging technologies to help its clients. Join Shailendra Kumar and team SAP in an interactive workshop to experience how organisations are becoming “Intelligent Enterprise”, leveraging data and analytics to deliver high value business outcomes.
    Hall 4: Workshops

  • 14:00 - 14:35
    How analytics will help and fail us, all while creating an increasingly uncertain world, and what you should do about it. During this talk we will discuss the impact of analytics on specific sectors and cross-sectors, using industry-specific use cases and student projects from the Jigsaw/Graham school classes to tell the story of the future impact and potential blind spots of analytics and why/how firms should be planning resilient and sustainable analytics strategies. Finally, we will discuss and provide attendees with an analytics innovation and risk playbook that can help them chart their analytics journey.
    Hall 2: Knowledge Talks

  • 14:30 - 15:05
    As AI technologies become more mainstream, an almost mad rush to embed AI both in businesses and everyday life is underway. What does this mean for Enterprises? Is it just about process automation or are there long-term opportunities? We believe the intersection of Data Science and AI holds immense potential for enterprises in terms of driving digital transformation outcomes. Let's simplify and contextualize what AI means for Digital Enterprises; let's look past the buzz and talk about making AI real for businesses.
    Hall 1: Keynotes & Panels

  • 14:30 - 15:30
    To date, Natural Language Processing (NLP) has been extensively deployed in the domain of online media – Twitter, Facebook, news and other widely available text resources such as IMDb movie reviews, Reuter’s data, etc. Different problems such as topic modeling, entity recognition and sentiment analysis have been tested and benchmarked on such standard “generic” datasets. However, specialized domains such as biomedical text have their own complexity. Biomedical data sources have a number of characteristics that make it difficult for using NLP – such as the presence of parenthesized text, lack of tagged standard data and therapeutic area variance, information in tables and figures (which are usually difficult for NLP to handle). At ZS, the Advanced Data Science team is at the forefront of solving these challenges and building new applications to drive efficiency in trial operations. In this workshop, we will walk participants through how AI (and NLP in particular) is transforming the pharma R&D landscape. We will then deep-dive into a specific challenge - biomedical entity recognition. Participants will be acquainted with multiple state-of-the-art methods such as Conditional Random Fields and Deep Learning that are currently being used for Biomedical Named Entity Recognition.
    Hall 4: Workshops

  • 14:35 - 15:10
    Hall 3: Masterclass & Talks

  • 14:35 - 15:10
    Training deep neural network models requires a highly tuned system with the right combination of software, drivers, compute, memory, network, and storage resources. Deep learning frameworks such as TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have contributed to the popularity of deep learning by reducing the effort and skills needed to design, train, and use deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) provides a consistent way to run these deep-learning frameworks as a service on Kubernetes. In this talk ,I will be introducing a framework called  Fabric for Deep Learning (FfDL). It uses a microservices architecture to decoupling components, making component simple & stateless, isolate component failures and allowing each component to be developed, tested, deployed, scaled, and upgraded independently.
    Hall 2: Knowledge Talks

  • 1400 - 14:35
    Various patterns emerge out of customer behaviour how critical it is to identify the key behavioural patterns and use them appropriately to generate insights which could significantly impact merchandising decisions is the key, which is what I am going to talk about at Cypher.
    Hall 3: Masterclass & Talks

  • 15:05 - 15:40
    Data Analytics is now infused in places where it never existed before, this has not only transformed the information aspect into the overwhelming ‘Big Data’ but also increased the demand of analytics as a driving factor for modern business operations to derive predictive and prescriptive insights. Digitalization has shifted data gravity to the cloud bringing another challenge of providing “analytics everywhere.” This significant shift from real to the virtual world has enforced IT to envision an end-to-end architecture that can holistically manage data and convey advanced analytics for lower TCO & higher ROI. The current scenario requires data, analytics, and action to be provided by a cohesive tool to satisfy the competitive business hunger. BDB Decision platform is designed with the above requirements in mind to incorporate diverse data including that of generated through the cloud and deliver profound analytical insights to the end users on any device. BDB Decision Platform with its below listed integrated capabilities can become a one-stop solution from data consumption to insight discovery for all the modern organizations: Data Ingestion- A real-time pipeline to support batch wise and streaming information Data Preparation- A devoted tool to identify data anomalies and perform in-depth data purification Analytics - Powerful Predictive Workbench with Neural Network support to get you a customized advanced analytics model Visualization- Splendid visual reports and dashboards to represent your findings Data exploration - AI Driven NLQ enabled text and voice-based responsive ‘Search’ to let you penetrate through your data layers to unveil the hidden insights Mobility- Native Mobile Apps fully integrated with the Decision Platform allowing you to access your analytics from everywhere Experience our cohesive Decision Platform in Cypher-2018 to understand it better.
    Hall 1: Keynotes & Panels

  • 15:10 - 15:45
    In the last few years, a range of powerful market forces and competitive imperatives have driven insurers across the industry to embrace advanced analytics. As insurance companies address key strategic, operational and technical issues embracing a holistic approach to developing their analytic capabilities. require fundamental and coordinated change across every phase of the project life cycle. The evolution of application of technology is reshaping the insurance industry. Application of new technologies by the insurance companies are improving their operating models, upgrading their propositions, and developing innovative new products to reshape the insurance industry as a whole. Five key technologies driving the change today and shall be having deep impact in coming days are– Cloud computing, The Internet of Things (including telematics), Big data, Artificial intelligence and Blockchain
    Hall 3: Masterclass & Talks

  • 15:10 - 15:45
    Join Anirudh Shah (Founder & CEO, 3LOQ Labs) to learn how his company 3LOQ is solving the problem of customer churn with machine learning technology. 3LOQ addresses this challenge by deploying proprietary machine learning algorithms to analyze billions of data points and map out dynamic feature recommendations to reinforce repeated usage of a product. The end result? Reduced churn with high customer engagement for businesses. 3LOQ partnered with a leading Indian bank to implement an AI-based solution to increase adoption of their digital channels. The project yielded impressive results, including: · A reduction in customer churn · An increase in digital banking transactions · An increase in users who made four or more transactions per month In this knowledge talk, Anirudh Shah will share his company's experience of building a holistic AI solution with the client, as well as major takeaways for businesses seeking to do the same.
    Hall 2: Knowledge Talks

  • 15:50 - 16:50
    #JustGetWeather The workshop will provide insights into how weather data is being used by clients across many industries to demonstrate the use of historic and forecast data as-is and in predictive models. The use cases will reflect real world scenarios for which solutions have been built to help optimize operations, reduce costs, improve safety, and uncover new revenue opportunities. We will also take an interactive approach to hear from you on how weather data relates to your business, the impact it can have and what business questions can potentially be answered partly or completely by weather. There is something every business can do about the weather. Want to know more? Join our workshop to explore.
    Hall 4: Workshops

  • 16:00 - 16:35
    Traditional Machine Learning Model required significant amount of mathematical analysis and non-scalable inputs from the business users in data analysis and preprocessing, making the business very difficult to scale up. Hence, the team demanded to be eminently skilled and educated in domain and mathematics. However, the contemporary deep learning strategies, by changing the paradigms from feature engineering to feature learning, made implementation a lot more scalable and engineer friendly. We will discuss the important paradigm shift that has happened in the past 5 years causing the investments in AI come down, but output and performance go up simultaneously, resulting in ROI soaring much higher than it was 5 years back.
    Hall 1: Keynotes & Panels

  • 16:05 - 16:40
    In this talk, we’ll discuss few key principles and practices that will help practitioners to build better machine learning systems. When we’re building a model, we’ve to make assumptions about the process that generates the observed data. Faulty assumptions will lead to incorrect predictions. We’ll discuss about the principle of maximum entropy that can aid us in evaluating the assumptions we include in the model. Once we deploy a model in production, it is critical to analyze the results thoroughly. We’ll discuss the role of dimensional analysis in uncovering where your model is working well and where it is not.
    Hall 2: Knowledge Talks

  • 16:35 - 17:20
    The Analytics and Decision Sciences organisation at Flipkart has the charter of leveraging science to enable robust data-driven decision-making. Key focus areas of this organisation are business growth and continuously improving customer experience. My talk will present the overall landscape of the Analytics organisation and the areas we cover. Use cases will be presented in the areas selection, pricing and customer experience
    Hall 1: Keynotes & Panels

  • 16:40 - 17:15
    In recent years, a number of business segments have successfully used big data and advanced analytics to enhance revenue performance. Numerous technology changes are driving new challenges to revenue management. This case study revolves around changing trends in hospitality and car parking industry. What remains common throughout the revolution of these trends is data. Accurate data insights helps you make right decision at the right time. Seeking to Optimize overall profit at Hotel and Carparks, it is necessary to understand the story that your data is telling you. This is where the real challenge starts as your data may not tell you the complete story. In this session, let’s zoom a bit and also look through the lens of future and determine what could be the changing trends in Hospitality and Car Parking.
    Hall 2: Knowledge Talks

  • Day 2

    Sep 27, 2018

  • 09:15 - 10:00
    Organizations are harnessing the power of information not available previously; technologies to process information at larger scales; techniques to drive personalized & granular insights. As organizations embark on this transformation they are grappling with some harsh ground realities – lacking the required capabilities. Conventional Analytics Training is failing to fill this gap and hence we declare this dead. In this talk we explore & present Analytics Training 2.0 to truly build capabilities and enable organizations to become data smart.
    Hall 1: Keynotes & Panels

  • 10:00 - 10:35
    India presents a big challenge and an opportunity for AI at scale. Right from the availability of quality data to having strong data science skills, companies are in constant search for resources. There is a significant pressure on IT Service Providers to show quick results, with quality. Having spent some time now in this space, the speaker will talk about where we are today, some of the gaps that need to be addressed, a few use cases that customers have been exploring or has been implemented and IBM's on-premise AI offering PowerAI.
    Hall 2: Knowledge Talks

  • 10:00 - 11:00
    Estimating the shape, pose and movement of humans in images or video is a basic problem in computer vision, and when properly solved, will enable applications ranging from video surveillance and sports analytics to AR and VR. In this talk, we will look at how far we have come with human sensing using Deep Learning. For instance, we can now do very high-quality 3D human pose estimation, a task that was unthinkable without using Deep Learning based algorithms. While major challenges still exist, we will explore how we can get past the roadblocks and advance our ability to build ever more functional applications.
    Hall 4: Workshops

  • 10:00 - 13:00
    Summary: IOT is making inroads into almost every business domain with billions of connected devices generating huge amounts of data. In this session, we’ll explore how IOT applications are being powered using Analytics and ML. We will start with an Introduction IOT and its business implications, then discuss IOT architecture and analytics and ML in the context of IOT. You will also get chance to build your first end-to-end IOT application using your Android phone and IBM Watson platform. Coverage: Introduction to IOT & Business implications IOT Architecture and Analytics and Machine Learning in the context of IOT Hands on: Build your first IOT application using IBM Watson and a smartphone Session infrastructure requirements: Projector WiFi for all participants Participants to bring their smartphones and charged laptops for the Hands-On part
    Hall 3: Masterclass & Talks

  • 10:00 - 10:35
    Hall 1: Keynotes & Panels

  • 10:35 - 11:10
    Organisations across the world are embracing AI in different ways and in our experience we see that the journey to AI is best achieved by ensuring a strong underlying data platform and information architecture. This session will talk about the foundational building blocks for climbing the AI Ladder and how leading enterprises are adopting a trusted analytics foundation based on a solid Information Architecture to build actionable business analytics, thereby progressing their AI journey.
    Hall 1: Keynotes & Panels

  • 10:35 - 11:10
    Going out for dinner in Mumbai during an extended stay, or planning for a long road-trip across the wild west of Rajasthan, the first thing one looks at is Maps, that informs the relative distance, estimated time and congestion areas of different routes for the drive. Zendrive built state-of-the-art technologies on its huge cache of driving data from smartphones and OBD, to add a significant dimension to the route mapping of Google, that is safety risk of the route. Essentially the technology is built on millions of drivers zipping through the route or segments thereof. Automobile Insurance expands in UBI- where it has been established that tracking a driver’s behavior behind the wheels (like Hard Brake, Speeding etc) can predict significant differences between their chances of collisions. Looking at the same event data from the road perspective, aggregating the relative event density on road stretches also predict the relative chances of collision on that segment. We have used map matching using GIS techniques, parametric density estimation and rare event modeling using quasi-Poisson GLM to analyze our data, build the models and finally implement the scoring system across the GIS route maps. Key learnings : Relation between dangerous driving events and collisions Route risk as an aggregate of all the drivers (or sample thereof) and their driving risk. The route you take for commute may determine your auto insurance. Outline : Usage Based Insurance : relation between collision rates and dangerous driving. Driving events : aggressive acceleration, hard brake, speeding, phone use, aggressive turns Poisson GLM modeling to predict collision rates using driving data Events on a road segment : map-matching using GIS techniques to split trips along road stretches, and aggregate such events along the spatio-temporal dimension across all drivers. Route risk of the road segment and any route comprising such segments. Driving risk along such routes and corresponding collision risks using transfer of the GLM model. Assignment of risks to drivers on their daily route of commute, to be used in UBI.
    Hall 2: Knowledge Talks

  • 11:10 - 11:45
    The Financial Services Industry deals with very large & rich customer data with numerous transactional touch points. Within the Financial services space, the Banking Industry which has tons of data both structured & unstructured, have to meet various challenges like customer engagement, opportunities to maximize the wallet share and having a good quality credit risk evaluation. The core focus area for most of the Analytics teams in the Banks are enhancing the organizational bottom-line and at the same time managing customer expectations. We will deal with couple of the case studies which are related to the credit risk analytics through structured and unstructured data and at another Data Science case study looking at an alternative way of looking at customer relationship value & the financial value being provided to the customer
    Hall 2: Knowledge Talks

  • 11:20 - 12:20
    Computer Vision in the Examination Hall Have you ever wondered what would it be like if the computers were invigilating exams? Examination malpractices remain a bother in the educational system. With so much of strictness being introduced inside the examination halls, which includes preventing the examinees to carry their own materials, putting students under active surveillance by multiple invigilators and even fixing CCTV cameras inside the examination halls, we are going to discuss what is the next thing we are likely to see in this practice. In this workshop, we will discuss a way to create a virtual examination supervision system that will be able to check the examinees throughout the period of the examination. Computers would be trained to detect ‘inappropriate’ motions of the candidates during an examination. We will talk about the algorithm introduced by Viola and Jones - ‘Rapid Object Detection using a Boosted Cascade of Simple Feature’, which is the foundation of the setup we have designed. The discussion will further include our journey and the critical challenges faced towards this first step in creating a robust virtual examination surveillance system. This is a capstone project done by students of PGP in Data Science at Praxis Business School. The workshop would be delivered by the students and their faculty guide.
    Hall 4: Workshops

  • 11:30 - 12:05
    The impact of analytics on business is changing dramatically - from Additive to Multiplicative to Exponential. The Evolution of Analytics Impact on Business: Impact = Analytics + Business [Additive: Analytics Support Business] Evolving To Impact = Analytics x Business [Multiplier: Analytics Drives Business] Evolving To Impact = Business ^ Analytics [Exponential: Analytics Transform Business] The resurgence of Artificial intelligence (AI) is at the heart of the analytics impact (r)evolution. Realizing the transformative impact of AI requires innovating at multiple intersections including Analytics & Technology, Data & Domain, Lab & Real-world, Science & Engineering; transforming cross-functional ideas into innovative business outcomes. Come join us at this session, where through a series of cross-industry case examples we will share our journey of innovating at the intersection to realize the impact of AI.
    Hall 1: Keynotes & Panels

  • 11:45 - 12:20
    The last few years have seen an explosion in the growth of data. As companies begin to rely more and more on analytics, it is essential that everyone in the organization learns to speak the same language - the language of data. This session explores what it means for an organization to be truly "data smart". It addresses the notion that analytics is not a niche skill for a select few. Rather it is a skill that needs to be embedded within the DNA of the organization where everyone, from the entry level executive to the C suite, needs to understand and respect the power of data and analytics.
    Hall 2: Knowledge Talks

  • 12:05 - 12:40
    We are the witnesses. To an era of human redesign. Artificial Intelligence, genetics, bio-engineering and nano-technology are merging our biology with our technology. This will change us and change everything about us. All our institutions, all our practices. And that includes love, sex and marriage. The ideal partner, need not be all human.
    Hall 1: Keynotes & Panels

  • 12:20 - 12:55
    Every day, digital users generate massive amounts of unstructured, interconnected data from social media, online portals, internal business processes, and other sources. Graph databases are particularly well suited for storing and deriving insights from these types of interconnections. Lets understand how to store interconnected data and run queries to gain insights using the OrientDB database. We will learn how to cleanse a data set, extract entities and relations, populate the OrientDB database, and execute queries
    Hall 2: Knowledge Talks

  • 12:40 - 01:15
    The various analytical initiatives taken by AP Govt and it's impact.The initiatives would cover various aspects like Hon'ble CM Real time dashboard, Fintech Valley vizag, Real time Governance, land records and also on introducing the exclusive future tech courses through an exclusive institute i.e IIDT.
    Hall 1: Keynotes & Panels

  • 13:30 - 14:30
    The workshop is focused on giving the attendees a hands-on experience on processing unstructured text data, as approached from different routes (Linguistics, Machine Learning and Data Mining). The workshop is designed in a LEARN | APPLY | SOLVE framework, which starts with a guided session led by experts with relevant industry experience and application of those learnings in a Virtual Lab environment with real business data. The workshop will be ideal for those who are working (or planning to start) in the areas of Text Analytics, Natural Language Processing, Machine Learning, Data Mining, Web Mining, Social Media Analytics etc. The workshop will be imparted through Analyttica TreasureHunt(ATH) http://ath.analyttica.com, a cloud enabled patented analytics solution platform that leverages the power of R, Python, and TensorFlow. As part of the workshop the attendees would be given free access to ATH for three months, including a detailed course on Text Analytics for continued learning. Note: This will be a Hands-on session, for a simulated learning experience. Please carry your laptop with internet access to get the most benefit out of our innovative Virtual Lab platform.
    Hall 4: Workshops

  • 14:00 - 14:35
    Value of analytics is growing by the day and we are improving each day in our capabilities of fetching insights from data. From statistics to cognitive, the journey is baselined by one simple requirement of having large amount of data. Adding to the flavour is the fact that technology is indeed generating an enormous amount of data. However, there is a gap in between. The gap created by ineffective data collection and management, manifesting as the problem of silos. Developing an ecosystem around the approach of attacking the problem has opened up new potentials and opportunities, accentuating the need of a more matured ecosystem, which may further beautify the data landscape.
    Hall 2: Knowledge Talks

  • 14:00 - 14:35
    Hall 3: Masterclass & Talks

  • 14:20 - 15:05
    This panel discussion is by Actify Data Labs – A True North Company Key discussion What are some of the areas in which AI and ML are making (or will make) the maximum impact for mid-sized organizations? What are some of the disrupters and how are mid-sized organizations better placed in disrupting their industries? What are the challenges in creating a culture of data driven decision making in mid-sized organizations? How is competition forcing mid-sized organizations to embrace the power of analytics, machine learning and AI? What are some of the challenges that are typical for a mid-sized organization: availability of talent, budget constraints, organization readiness etc.? How are some of the mid-sized organizations better placed to harness newer technologies – faster decision making process, absence of legacy technologies etc.? What are the options for embracing analytics, AI and ML for mid-sized organizations – build, buy, hybrid, etc. What are the key skills that an analyst should bring to the table to succeed in a mid-sized organization? Why is the journey within a mid-sized organization more interesting for both analysts and analytical leaders? Will a giant like Google or Amazon probably offer all standard analytical requirements in its analytics cloud and force all smaller products and services companies out of consideration for mid-sized organizations?
    Hall 1: Keynotes & Panels

  • 14:30 - 15:30
    Forecasting comprises of short-term and long-term plans and is critical for success of any business as it helps to maneuver future uncertainty. Short-term forecasting is used across industries to respond to their supply and demand planning needs. The short-term forecasting is critical as it ensures accuracy to minimize uncertainties and be agile to adapt to unforeseen situations. As the performance of forecasting methods strongly depends on multiple factors such as domain, frequency, length, characteristics and horizon, they make efficient short-term forecasting a challenging problem. In this workshop, we will cover framework and examples for driverless forecasting which aims to achieve accuracy and agility by using statistics and machine learning theory in practice.
    Hall 4: Workshops

  • 14:35 - 15:10
    In his session, Supratim will be elaborating on the following aspects: Data protection policy and laws in India Key challenges and loopholes in the existing framework Current discussion around draft data policy in India Suggested measure for the bill Brief comments on GDPR What Indian data protection law can adopt from GDPR How will it impact industries and companies in India
    Hall 3: Masterclass & Talks

  • 14:35 - 15:10
    The e-commerce industry has greatly evolved over the past decade, newer technologies, advanced computational power, big data analysis, machine learning, and digital marketing have substantially contributed towards this growth. Data analysis has played an important role to understand customers better and this has led to a paradigm shift in the industry. Data is no longer a by-product of the business model but can be considered as a key driver to understand customer behaviour, return on investment, and to formulate customer acquisitions and retention strategies. Machine Learning can help e-commerce retailers offer intelligence-powered shopping experiences to customers, increase conversions, and curtail cart abandonment. The average customer of today uses at least four devices – mobile, tablet, laptop, and a desktop daily. Smartphones are used to make online purchases. This topic would be focussed on different areas of machine learning and its application ranging from Assortment Planning, Marketing Analytics, Pricing Analytics, Smart Supply Chain Management, Promotion Planning, Product Development and Design. The topic also emphases on extensive application of machine learning in Amazon, Myntra, Walmart and HDFC. The topic would also cover multiple experiments carried out in different e-commerce businesses. Lastly, we will also cover the impact of Economic Conditions and Competitor Analysis in e-commerce domain.
    Hall 2: Knowledge Talks

  • 15:05 - 15:40
    Businesses compete. They compete for customers, human resources, partners, consumer mind share, market share, and more. Naturally, developing competitive advantages is a vital area of focus and a perpetual journey. Nowhere else is this truer than for the world of retail. In an ecosystem of shrinking margins and rapidly evolving consumer expectations and buying patterns, retailers need to consistently stay ahead of the curve to thrive. In this context, can AI and ML technologies be leveraged to address something as fundamental to the nature of doing business as gaining a competitive advantage? As businesses globally embrace the digital economy, the Web has emerged as the single largest source of competitive data. When this data is harnessed and analyzed to generate meaningful insights, it can drive smarter, market-driven decision-making. The applications are vast and compelling. Can retailers house a relevant and nuanced assortment of products for shoppers to choose from? Can these products be priced competitively, yet support profitability? Can consumer brands detect counterfeit versions of their products sold online? Can the consumer’s voice be distilled to generate quantifiable insights on their sentiments? This talk will explore these themes and demonstrate how AI and ML can give retailers just the edge they need to win against their competitors.
    Hall 1: Keynotes & Panels

  • 15:10 - 15:45
    Vinodh will be talking about how business context combined with analytics helps solve business problems more efficiently.
    Hall 2: Knowledge Talks

  • 15:10 - 15:45
    The “Sexiest job of the 21st century” is often surveyed to be poorly defined, intermittently satisfying and vaguely understood in most board rooms. As success stories are widely publicized, senior business leaders’ expectations from analytics are rising quickly. And the field itself is changing rapidly - with speciality skills becoming self-service in no time. In that context, the talk explores how the various analytics roles across the spectrum are changing. And what it takes for analytics professionals to stay relevant, contribute meaningfully to business results and play a critical role in shaping business strategy.
    Hall 3: Masterclass & Talks

  • 15:50 - 16:50
    This is hands on workshop. Please sign up for IBM Cloud https://ibm.biz/BdYqGm We can analyze the data and build prediction models which will help to identify risks involved in payment. The model will guide you to identify customers who are going to default in their payment based on their past payment history. You can either choose algorithm manual mode to do classification or Watson Studio can pick the right classification based on data (automatic mode).
    Hall 4: Workshops

  • 16:00 - 16:35
    India has one of the largest student numbers in STEM field. It also has vast number of engineers in corporate and government sector. Despite that India is known for providing lower end services and cutting edge international products are a rarity. In addition, despite tremendous growth in the start-up sphere, India is still nowhere in the list of top innovative countries. How can student and corporate training change that? Also what kind of products and policies should be pushed on a priority, to make the needed difference? In my talk, I would use my experience of citizen science in USA and India to chart out a territory. I would emphasize needed skills for corporate re-skilling, so India is prepared for the fourth Industrial revolution. Also, I would discuss a couple of examples from my dozen or so partnerships with start-ups involved in AI sphere. I would emphasize how development of few key AI technologies can promote efficient, ethical, and egalitarian use of social media, healthcare, and education to transform India.
    Hall 1: Keynotes & Panels

  • 16:05 - 16:40
    AI is slowing becoming mainstream. Every startup is looking for ways to incorporate AI in their products. Is there a method to do it? Come and listen to a few thoughts on how startups can leverage AI in their journey.
    Hall 2: Knowledge Talks

  • 16:35 - 17:20
    As data becomes integral to business and the much needed competitive advantage that companies will need to leverage in order to be successful, it brings with it a new set of challenges. With the growing demand for data scientists, there is a huge pressure on industry to find the professionals with the right experience and skill sets. In this session, we will speak with people from both sides of the table, companies looking to fill the gap and professionals looking for roles in data science. We will explore their different perspectives, the challenges they face, and discuss ways to address them.
    Hall 1: Keynotes & Panels

  • 16:40 - 17:15
    Traditional Engineering which is the backbone of Auto motives has been always relying on traditional physics, mathematics and natural sciences to deliver the world best of Designs and Products since 100 years. Engineers spend time, energy and knowledge to solve complex problems over years in the field of quality, safety and various processes beyond the much hyped driverless cars. This talk aims to provide a glimpse of how we can utilise Deep Learning and Computer Vision for Traditional Science, Potential challenges and the Products which can be developed through packaged Artificial Intelligence solutions in the field of Automobile Engineering.
    Hall 2: Knowledge Talks

  • Day 3

    Sep 28, 2018

  • 09:15 - 10:00
    In the age of industry 4.0 revolution, AI continues to dominate the technology landscape. Whilst the naysayers have advocated the doomsday for humanity by predicting the advent of singularity, AI for good & all have several applications to usher a new change in the country to solve large, complex and unresolved problems and challenges. Imminently, for the first time, there is an emerging competition and urgency by several countries and nations to embrace AI to tackle the challenges that are plaguing citizens. The talk session will focus on the gamut of steps that different countries are implementing to embrace AI , how India is uniquely positioned to attain leadership status in AI and thru the various policy initiatives by state and center governments , how several AI led interventions are being planned and implemented in India to race ahead in the AI arena. Eventually, Its “ AI for Humanity “ mantra for Make in India.
    Hall 1: Keynotes & Panels

  • 10:00 - 11:00
    Manufacturers spend a lot of time and money on deploying their marketing materials within the store to gain visibility and boost their sales. Often, the in-store marketing campaign suffers from poor execution and damage within the store which in-turn leads to poor ROI for manufacturers. Auditing the deployment of marketing materials is plagued by inaccuracy and lengthy turnaround times due to the extensive use of manual methods to audit these stores. Further, verification of the findings of these audits is a difficult and time-consuming process for manufacturers. Our proposed solution aims to increase the accuracy, while simultaneously reducing the turnaround times for these in-store audits by applying the latest in computer vision to make these audits objective and speedy. By using an advanced CNN architecture like Google’s InceptionNet, we train a neural network to detect brands and eventually different types of in-store displays. The output of the neural networks is used to automatically tag and score images from audits. Automating the process will also make the verification of these audits quick and easy for clients. This would save them critical time and arm them with timely information to react quickly to new developments in the market.
    Hall 4: Workshops

  • 10:00 - 10:35
    We started relying on the decisions made by deep learning models, however why it works and how it works are still big questions for most of us. We shall try to open that black box of deep learning which is essential to build trust for wide spread adoption. The speaker shall address the importance of feature visualization and localization in deep learning models esp. convolutional neural networks. He shares the results of applying methods such as activation map, deconvolution and Grad-CAM in healthcare.
    Hall 3: Masterclass & Talks

  • 10:00 - 10:35
    Amidst all the noise about the Internet of Things, decision-makers are often left wondering how they can leverage the power of increased connectivity. The list of potential benefits is long: operational excellence through process optimization, better decision-making, thanks to big data analytics, AI, Machine learning that improved productivity, safety and quality control, and so on. To reap the benefits, businesses will need agile information infrastructures and they will have to tackle some crucial concerns such as security, integration and data ownership. But apart from that, businesses will also need to experiment and build use cases. After all, IoT is not just a technical challenge, but also a question of business model innovation. IoT is fundamentally changing the way we do business. By connecting devices and sensors to the internet, we are entering an age where data analytics, connectivity, and automation are creating innovations and progress which were previously out of reach. As the Industry 4.0 and home automation movements gain more traction, we will see IoT devices and embedded systems becoming more and more prevalent in our daily lives. The businesses that understand the use cases and potential of IoT are the businesses that will likely drive innovation over the next 10 years. The talk will go into the applications of IOT, Big Data, AI in varied sectors and applications and how these are changing the paradigm in these sectors and the benefits reaped by them.
    Hall 2: Knowledge Talks

  • 10:00 - 10:35
    Artificial Intelligence is slowly getting its way into organisations. AI journey can be quite complex and a proper roadmap would be needed to realize the benefits. This presentation will talk about common myth and a high level approach for bringing AI into the enterprise.
    Hall 1: Keynotes & Panels

  • 10:35 - 11:10
    Although not untouched by the advancements in technology, Legal domain is usually not considered to be an early adaptor. Barring the usual administrative functions, the practice of law requires significant cognitive capabilities of a human mind along with its greater problem solving capabilities. Although a wider conclusion rules out the usage of AI in this field, there are few tasks for which AI can provide a reasonable conclusion in this field. Even though the results may not be always accurate, but any instances where approximation is acceptable AI can possibly help in a great way to reduce human dependency and their intelligence driven decision making ability. The discussion is based on a project carried out as part of an academic requirement which tries to provide a framework for prediction of the legal outcome and also tries to analyze how the results can help augmenting the decisions taken by the para legal experts.
    Hall 2: Knowledge Talks

  • 10:35 - 11:10
    At HDFC Life, we have established a specialised Data Labs to deliver innovation and drive value creation using data science. We aim to create a technologically efficient mid office to manage anything the front end sales team brings to it or anyway the customer wants to deal with the organisation.
    Hall 1: Keynotes & Panels

  • 10:35 - 11:10
    Product Discovery remains one of the biggest challenges for fashion e-commerce. In an offline world a user can ask for "a fancy night out mini-dress with pretty detailing" The store manager will show the user some products, improvising the recommendations with user inputs and will help match the dress with heels and other accessories.
    Hall 3: Masterclass & Talks

  • 11:20 - 12:20
    Hall 4: Workshops

  • 11:30 - 12:05
    Banks and MSMEs are achieving business development and financial inclusion, leveraging Statistical techniques and Advanced Analytics viz. · Product and Process Optimization through Analytics, alongwith recent changes in MSME regulations (GST, UAN, Insta Facility, etc) · How Business Analytics is efficiently managing and driving MSMEs into profits (resource allocation, pricing and revenue, etc)
    Hall 1: Keynotes & Panels

  • 11:30 - 12:05
    With the advent of citizen data-scientists, Artificial Intelligence (AI) algorithms are being applied to a very large number of problem statements to narrow down on those that really create value for organizations. Such applications begin with experimental study or proof-of-concept (POC) along the lines of what many of you may have seen on Kaggle.com and are then productionized as a part of scaling and embedding in business processes. While data scientists take the lead role in the model development phase, Machine Learning (ML) engineers take over during the productionizing / operationalization phase tackling a completely different set of problems such as ML model management, optimization and deployment, etc. In this session, we will walk you through the AI/ML process being followed within enterprises today and the differing needs of data scientists and AI/ML engineers that need to be catered for helping enterprises succeed in this space. We will also describe a reference model life cycle and discuss real life challenges, solutions and learnings from our joint implementations for clients.
    Hall 2: Knowledge Talks

  • 11:30 - 12:05
    Amazon Alexa, the cloud based voice service that powers Amazon Echo, provides access to thousands of skills that enable customers to voice control their world - whether it’s listening to music, controlling smart home devices, listening to the news or even ordering a pizza. This talk will serve as an introduction to the Amazon Alexa and the Alexa Skills Kit while illustrating why Voice is the next major disruption in computing. The talk includes a hands-on demo of the entire skill building process. You will also learn how the Alexa cloud service works as well as best practices in voice design.
    Hall 3: Masterclass & Talks

  • 12:05 - 12:40
    Pink Floyd in their iconic song "Brick in the Wall" had stated that "we don't need no thought control .." but the time has come to talk about Thought Control of Machines. The interface between man and machine has traversed a long trajectory from key boards to touch screens and voice activation but now we are heading into an era where we are already controlling machines by thought alone. This concept and technology will be explored in this session
    Hall 2: Knowledge Talks

  • 12:05 - 12:40
    “The upheavals [of artificial intelligence] can escalate quickly and become scarier and even cataclysmic. Imagine how a medical robot, originally programmed to rid cancer, could conclude that the best way to obliterate cancer is to exterminate humans who are genetically prone to the disease.” — Nick Bilton, tech columnist wrote in the New York Times” Data Science as a skill and Data Scientist as a role have been in the market for more than a decade now. It is high time to ponder that what is required from a data scientist. Since, Data Science is a highly disruptive industry which demands continuous upskilling and reskilling from an industry perspective. The entire business has moved from just building models and generating insights to build real time applications and platforms. The likes of building smart cars, space cars, cancer prediction through AI and identifying and catching criminals through AI devices are some of the recent developments in the field of technology. Artificial Intelligence, Deep Learning, IoT totally fit as a robust mechanism to provide such solutions for the businesses. How do you build such skills? The traditional model of reskilling seeks a theoretical approach to build AI and Deep Leaning competency. Hence, it is important to bridge the gap through an amalgamation of concepts, applications and flavor of businesses. Companies such as Intel, Google, Microsoft, IBM, Tesla, NVDIA are the innovators in the space of building solutions in AI, IoT and Deep Learning. Recently Gartner presented a detailed analysis of AI disruption in the market. "AI promises to be the most disruptive class of technologies during the next 10 years due to advances in computational power, volume, velocity and variety of data, as well as advances in deep neural networks (DNNs)," said John-David Lovelock, research vice president at Gartner. Business executives will drive investment in these products, sourced from thousands of narrowly focused, specialist suppliers with specific AI-enhanced applications." It is important to deploy experiential learning vehicles in collaboration with innovators to reskill the existing pool of data scientists. It is important to design, learn and apply from a 3-layered learning architecture. Layer 1 – Inclusion of conceptual training through digital platforms Layer 2- Engagement through in-person training workshops Layer 3 – Capstone Project in partnership with industry innovators. The talk is primarily emphasized on ways to reskill Data Scientists in newer and emerging technology.
    Hall 1: Keynotes & Panels

  • 12:05 - 12:40
    Our everyday life is dominated by powerhouses of AI/ML that started off small and grew big in different domains across transportation, food delivery, retail, e-commerce etc. This talk focuses on the common themes that cut across these domains and the importance of evolving to system thinking from model thinking illustrated through real-life examples of the journey from ideation to impact.
    Hall 3: Masterclass & Talks

  • 12:40 - 13:25
    There is no doubt that diversity helps companies generate significant improvements in growth. In this session, we will speak with leaders in analytics to focus on why it is very critical to advance the participation of women in data science and analytics roles and how we can enable that participation.
    Hall 1: Keynotes & Panels

  • 13:30 - 14:30
    The workshop will empower you and get started with analyzing text data, discover patterns and what are the best ways to convert unstructured to structured data. We will also build a quick classification model and understand techniques to improve model performance. Towards the end lets quickly do a sentiment analysis on data corpus and discuss the next steps to improve model accuracy. Please come prepared with a working laptop with Jupyter Notebook and Python 2.7. Participants who have a minimum working knowledge of supervised models is encouraged.
    Hall 4: Workshops

  • 14:00 - 14:35
    Hall 2: Knowledge Talks

  • 14:30 - 15:05
    “Digital” is an aspirational agenda for most organizations across all sectors, geographies and sizes. Every organization wants to harness the potential of different technologies at our disposal today. This agenda is more often than not, a top down mandate. How then, do we ensure that we are “Digital” ready for the next wave of industrial revolution? Thoucentric through its rich functional and domain experience across industries, complemented by a passionate analytics team, helps clients embark on their Analytics journey. We partner with them through their transition- from defining problems, to solutioning through effective hands-on execution across functional domains. Equipping supply chain with the right analytical assets has never been so important. There has been a paradigm shift in the way Supply chain is looked at in the organizations and the value it can bring to the top and the bottom line, not to forget the sustainability. Thus, it is imperative for organizations to understand how analytics can transform the Supply Chain.
    Hall 1: Keynotes & Panels

  • 14:35 - 15:10
    - Define relevant use cases for your industry - How staffing and organisational capability plays a role? - Keeping right expectations on ROI (Return on Investment)
    Hall 2: Knowledge Talks

  • 15:10 - 15:45
    Artificial intelligence is poised to unleash the next wave of digital disruption, and companies should prepare for it now. There are real-life benefits for a few early-adopting firms, making it more Important than ever all sectors to accelerate and adoption to their digital/IOT transformations. Five AI technology systems to focus is on robotics and autonomous vehicles, computer vision, language, virtual agents, and machine learning, which includes deep learning and underpins many recent advances in the other AI technologies. Early evidence suggests that AI can deliver real value to serious adopters and can be a powerful force for disruption. Early AI adopters that combine strong digital/IOT capability with proactive strategies have higher profit margins and expect the performance gap with other firms to widen in the future. AI promises benefits but also poses urgent challenges that cut across firms, developers, government, and workers. The workforce needs to be reskilled to exploit AI rather than compete with it.
    Hall 2: Knowledge Talks

WHERE

Hotel Radisson Blu
Bangalore, India

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