From: 17 Sep 2020 To: 18 Sep 2020

Start Time: 08:15 AM End Time: 05:15 PM

Venue: Novotel Bengaluru Outer Ring Road,Outer Ring Road Opposite Rmz Ecospace Business, Park, Sarjapur Main Rd, Marathahalli, Bengaluru, Karnataka 560103

Created By: 1.21 Gigawatts

Ticket Type Ticket Price Seat Quantity Available Seats
WORKSHOP ONLY (STANDARD PRICE + GST )[Till 16th September, 2020] ₹15000.00 INR 20 Available
GROUP OF 3 OR MORE (ANY ONE DAY + GST )[Till 17th September, 2020] ₹8000.00 INR 20 Available
PROMOTIONAL PRICE (BOTH DAYS + GST )[Till 30th May, 2020] ₹12000.00 INR 20 Available
ANY ONE DAY (STANDARD + GST )[Till 17th September, 2020] ₹9000.00 INR 20 Available
ANY ONE DAY (STANDARD + GST )[Till 17th September, 2020] ₹15000.00 INR 20 Available

Total amount INR:



Event Description

Briefly Know About This Event
We are very excited to announce our 3rd edition of World Machine Learning Summit-2020, India being organized by 1point21GWs, stay ahead with us!

World Machine Learning Summit is a 2 day conference in Bangalore from 17 - 18 September, 2020. This is a Program being curated based on guidelines from industry experts, with a target of about 500+ delegates.

What To Expect :

Day 1: 17 September, 2020
Track 1 : Tools, APIs & Frameworks
Track 2 : Applications

Day 2: 18 September, 2020
Track 1 : Trending
Track 2 : Deep Learning

Who Should Attend :
? Data Engineers/Developers / Scientists
? Analytics Professionals
? Startup Professionals
? Scientists/Researchers
? Professors
? President/Vice president
? Chairs/Directors
And last but not the least???.
? Anyone interested in Machine Learning & thrives to make the future developed and better

08:15AM ? 08:45AM RPA Olympiad 2020 - Semi-finals
schedule 08:50AM ? 09:10AM Registration / Conference Overview
Nitesh Naveen, Founder, 1.21GWS
schedule 09:10AM ? 09:50AM Application of multiple AI and ML techniques to solve real world use cases - Click Here for More Info
Manisha Banthia , Director, Fiserv Global Services

schedule 09:50AM - 10:20AM Tea Break
10:20AM - 11:00AM Tools, APIs & Frameworks : Deep NLP - Helping to break the Language barrier - Click Here for More Info
Biswajit Biswas, Chief Data Scientist, Tata Elxsi

Applications : Using data based insights to drive customer experience - Click Here for More Info
Dipayan Chakraborty, Head, Analytics & Insights, Myntra

11:00AM ? 11:40AM Tools, APIs & Frameworks : Recommender systems - Click Here for More Info
Rudrani Ghosh, Director, American Express Merchant Recommender and Signal Processing team

Applications : Data science and Machine Learning platforms - Do you need one for your ML projects? Learn how to decide? - Click Here for More Info
Vinod Khader, Associate Director, Watson Machine Learning Platform Development, IBM

11:40AM - 12:20PM Tools, APIs & Frameworks : Smarter personalization, Machine Learning & UX - Click Here for More Info
Sameer Chavan, Senior Director & Head of Design, Flipkart

Applications : Reinvent Banking with Machine Learning. - Click Here for More Info
Mathew Joseph, Vice President & Head of Data Science Lab (CIMB bank), Apar Technologies Pvt. Ltd

schedule 12:20PM ? 01:20PM Lunch Break
01:20PM ? 02:00PM Tools, APIs & Frameworks : Demo on VQA implementation for 20-30 mins - Click Here for More Info
Karthikeyan NG, Director of Engineering, Sequoia Consulting Group

Applications : Practical implementation of Auto ML - Click Here for More Info
Anjanita Das, Associate Director, Cognizant

02:00PM ? 02:40PM Tools, APIs & Frameworks : AI & ML implementation examples at TVS Motors - Click Here for More Info
Anand Das, Head of data science & engineering (Consumer and channels), TVS motors

Applications : Interpretability of Machine Learning Models - Click Here for More Info
Hitesh Hinduja, Data Scientist (Manager), Ola

2:40PM - 03:20PM Tools, APIs & Frameworks : Identification of high performing Contextual Strategies for Digital Advertising - Click Here for More Info
Manish Pathak, Data Scientist II, MIQ Digital India Pvt. Ltd

Applications : Practical examples of how we are making it possible - Click Here for More Info
Wessel Oosthuizen, Associate Director ? AI Lead, Deloitte

schedule 03:20PM ? 04:00PM Tea Break
contest 04:00PM ? 05:15PM RPA Olympiad 2020 - Finals
Day 2: 18th September, 2020
Track 1 : Trending
Track 2 : Deep Learning
XTopic Abstract

In business areas where there are decisions involved that have social implications and we have seen biases in human decisions or data skewed undesirably towards a particular category, it is important that our ML/AI algorithms are tuned to eliminate any such bias that are bound to creep in automatically due to historical data. How to we identify those scenarios and eliminate biases effectively from our Machine Learning algorithms.

Speaker Profile

Manas heads the Wealth Technology Business Unit for ANZ Bank in Bengaluru, a man with diverse interests apart from his role in Technology Delivery ? a passionate champion of Innovation, he has helped institute an Innovation Framework in ANZ Wealth Globally including an Innovation Contest that is saving hundreds of thousands of dollars. Manas is also the Chair of the ICT-Academia Expert Committee of Bangalore Chamber of Industry and Commerce (BCIC), where he is presently leading the organisation in a number of Industry-Academia initiatives.

Speaker Profile

I am an Associate Director with more than 9 years? experience in data and analytics. I am part of Deloitte Analytics, a cross-functional team with a focus on embedding data and analytics and AI in organisations across Africa. I am also responsible for the Digital Transformation team in Risk Advisory with a focus on exponential technologies, AI, Digitisation and rapid prototyping. I am passionate to help people on their journey to enable their company to become a data driven organisation, and have a passion for moving Africa into the fourth industrial revolution and enabling the true potential.

XTopic Abstract

XTopic Abstract

Service Desks requires good strategy and innovation to improve customer service and to support business goals. Cisco TAC is constantly looking at ways to provide customers with the information they need via a self-service capability in an attempt to reduce the number of support requests that are opened. This is frequently referred to as case avoidance. A significant amount of information is lost while exchanging mail, chats or over case notes.

The impediment to progress is the inability to derive actionable insights from this unstructured text since most of the prioritize corrective action is buried in these notes. Using advanced ML techniques along with text mining solution, the objective is to extract actionable insights for TAC that can be used to drive down Service Request volume. The proposed solution comprises of text parser and automated case deflection Conversational NLP solution which can provide an immediate solution using historic data analysis"

Speaker Profile

Vivek is currently a data scientist @Cisco. He has 7+ years of work experience across E-commerce, mortgage, Retails and CPG domains. He is an extensive NLP researcher, he has a pragmatic approach in text mining, NLP, Machine learning and social media analytics. Prior to Cisco, he has also worked across organizations like Xerox, BRIDGEi2i and Altisource.

XTopic Abstract

Glimpse of computer vision
Primer on openCV framework
What is Sikuli framework
Showcasing real life examples using sikuli
An example being how to extract data and send emails all in a single click
How to use your python skills in RPA
Based on available time few more examples that can be easily understood by participants

Introduction to Automation Anywhere community edition
Speaker Profile

Bharathi is a Principal engineer with AT&T Communication services India ltd. He works in the 4G and 5G space who is a pioneer in RPA and also in AI field. He is also a PYTHOnator who like to transform the industry. Under his mentorship, hundreds of people (from students community and also from the industry) got into the bandwagon on Python and automation. He holds more than 78 awards within his company and also holder of THREE nanodegrees from Udacity (all in AI field). He loves to develop Alexa based skills as his hobby and ready to embrace new challenges every day.

XTopic Abstract

In this talk, we will cover the basic of Deep Learning and how to implement it hands on for text, images and videos. We will take 3 problems in Machine Learning for text, images and video and build classifier using Deep Learning. We will talk about different architecture like LSTM, CNN for treating images and video. The key take away from this talk is to get the basic architecture of Deep Learning and how to implement them in pytorch to do basic text or image classification.

Speaker Profile

I am a deep learning researcher, after graduating from Indian Statistical Institute with Master's in Computer Science, with specialization in NLP and IR, I have worked with Bing Ads, Microsoft R&D and HSBC Bank as decision scientist to build risk models for bank. I am currently working in Amazon as a data scientist to build models to cater to amazon internal network.

XTopic Abstract

Introducing latest development in NLP systems which enhances the usability and reliability of Conversational AI powered applications, especially in Customer Support systems like Smart IVRs and AI Chatbots. Also, how to go about adding support for Vernacular languages to increase customer engagement.

Speaker Profile

Nishant is an experienced Big data stack developer working at Microsoft Azure Storage Platform team. He has been instrumental in research for developing Vernacular Language Understanding Infrastructure for Indian languages using latest advancements in NLU domain.

XTopic Abstract

TV advertisement has always been the most preferable medium for marketers to reach a mass audience. Since the inception of smart/connected TVs, now we have access to second by second viewing data of households about their TV watching behaviour with the consent. At MIQ Digital India Pvt. Ltd. we collect this data in realtime with a scale of handling millions of requests per second and wrangling collected data as per the marketers need by retargeting TV viewers based on their demographics on digital medium across different channels. Automation Process looks at the intent of marketers targeting relevant audiences encapsulated by configuration . In order to achieve seamless processing, this particular data science solution is supported by Golang and Pyspark to achieve concurrency and accuracy for TV viewer segmentation.

Speaker Profile

Parth is currently a Senior Data Scientist at MIQ Digital India Pvt Ltd. He designs algorithms for finding similar users based on their Connected TV viewing pattern, predicting TV show tune-in, etc. With past experience of working on a varied set of data science problems in the field of Customer support, Revenue prediction, Customer churn prediction for subscription based business. He has completed his Masters in Technology with a Data science major from IIIT Bangalore.

XTopic Abstract

Leading EHR provider business wanted to leverage NLP & AI to optimize their efforts and mitigate risk

The support team of a leading US based Healthcare provider is responsible to identify any Priority STUBs out of all the STUBs raised and report it to the regulatory body within 7 days from the STUB raise date

XTopic Abstract

Insurance has been a traditional, century old business affair and has largely been unperturbed through the immense technological disruptions & advancements that have been made in the last decade or so. It has to take a leap of faith to evolve out of the traditional models of insuring property, casualty and commercial line items through leveraging AI & emerging technologies such as distributed ledger blockchain in order to revamp its presence to customers My talk will focus on my work in niche microinsurance based product offerings which are tailor made for a focussed audience group, such as: - Easy-to-purchase flight delay insurance using blockchain architecture (ref. focussing on millenials and frequent flyer groups - Usage based motor insurance as per the driving behaviour & risk score of the user - Parametric event interruption insurance (such as rains during cricket match etc.) I shall specifically stress on how are we building active machine learning workflows in designing the experience these products cater to their users while also touching upon the architecture which makes it feasible for implementation and monitoring production in the long run.

Speaker Profile

Amitanshu heads the New Products and Business Initiatives team at Bharti Axa General Insurance and has a diverse experience in speaking at various data science keynotes for corporates and student groups alike.

After completing his bachelors in Mathematics and Scientific Computing from Indian Institute of Technology, Kanpur (IITK), Amitanshu has extensive experience in both academia and corporates ? where he worked across verticals such as Telecommunications, Retail, E-Commerce and Insurance.

In his current role, Amitanshu leads the development of innovative micro-insurance product portfolios encompassing delays (flight delay insurance, cab trip delay insurance etc.), consumer durables & electronics such as gadget insurance, bicycle insurance etc. offering seamless customer claims experience with minimal customer involvement or paperwork.

Prior to this, Amitanshu has lead the end-to-end development & deployment of various Data Products leveraging sophisticated Machine Learning Algorithms on various fronts viz. Chatbots, Voicebots, Recommender Systems etc.

On a typical work day, you can find Amitanshu busy in strategizing optimal insurance cross-sell/up-sell strategies along with hands-on problem solving with Data Science & Product teams while implementing robust data architectures for optimum digital-first insurance product offerings. Apart from work, Amitanshu is a professional guitarist, with a passion for classic rock bands such as Pink Floyd, Led Zeppelin, Radiohead, etc. and an avid adventure sports enthusiast.

XTopic Abstract

What makes explainability difficult in AI/ML

How to go about adding explainability and interpreting it

Adding MLI (Machine learning interpretability) to Deep Learning models across text and vision projects

Pros and Cons of adding MLI in AI/ML models

XTopic Abstract

NLP based virtual agents are servicing robo advisory, be it explanation of financial products or of health plan benefits. The use cases will discuss on importance of interplay of ML and conventional engineering to solve end user problems, and explore an NLG approach to tackle the data non-availability issue for training purposes.

contest 08:15AM ? 08:45AM Machine Learning Olympiad 2020 - Semi-finals
schedule 08:45AM ? 09:10AM Registration / Conference Overview
Nitesh Naveen, Founder, 1.21GWS
09:10AM ? 09:50AM Trending : Ethics in AI/ML - Click Here for More Info
Manas Dasgupta, Head of Wealth technology, ANZ Bank

Deep Learning : Building a data science centre of excellence - Click Here for More Info
Wessel Oosthuizen, Associate Director ? AI Lead, Deloitte

schedule 09:50AM - 10:20AM Tea Break
schedule 10:20AM - 11:00AM Trending : Building Next Generation Scalable AI Platform - Click Here for More Info
Dr. Rahul Ghosh, Research Director ? AI Products, American Express AI Labs

Deep Learning : Demo: Python +ML - Click Here for More Info
Jyothish Joseph Cherian, Technology Manger, Wells Fargo

schedule 11:00AM ? 11:40AM Trending : NLP accelerated customer experience - Click Here for More Info
Kumar Vivek, Data Scientist, Cisco Systems(India) Pvt. Ltd

Deep Learning : Advancement in Deep Learning - Click Here for More Info
Bharathi Athinarayanan, Senior Technical Consultant, AT &T Mobility

schedule 11:40AM ? 12:20PM Trending : Quantum Computing: a Treasure Hunt, not a Gold Rush

Deep Learning : Hands on session on Deep Learning - Text, Image and Video - Click Here for More Info
Debjyoti Paul, Data Scientist, Amazon

schedule 12:20PM ? 01:20PM Lunch Break
01:20PM - 02:00PM Trending : State of the art, Production ready NLP systems and research areas - Click Here for More Info
Nishant Goyal, Microsoft

Deep Learning : Real time Ad retargeting based on connected TV data - Click Here for More Info
Parth Savjani, Senior Data Scientist MIQ Digital India Pvt. Ltd

02:00PM - 02:40PM Trending : Harnessing AI & ML for Prescriptive Analytics - Click Here for More Info
Madhav Kaushik ,VP, Client Solutions and Product Strategy, Analyttica Datalab Inc

Reimagining Insurance using ML & AI - Click Here for More Info
Amitanshu Gupta, Head, New Products & Strategic Initiatives, Bharti AXA General Insurance

schedule 02:40PM - 03:20PM Trending : Machine Learning Interpretability - Click Here for More Info
Amit Sharma, Director - Data Science, Part of Global AI Accelerator Team, Ericsson

Deep Learning : NLP and NLG in Virtual assistants - Click Here for More Info
Kapil Mohan, Director, Optum

schedule 03:20PM ? 04:00PM Tea Break
contest 03:40PM ? 05:15PM Machine Learning Olympiad 2020 - Finals
Pre Conference Workshop Schedule (September 16, 2020)
XTopic Abstract
? Automation Continuum & RPA
? Approach to RPA
? Selection of Tool
? Selection of Processes
? Measuring RPA Maturity
? Why RPA projects fail?
? Establishing RPA CoE
? Future of RPA & Other Cognitive Technologies
? Discussion on 1-2 case studies with demonstration
Speaker Profile

An alumnus of NIT Bhopal and Warwick Business School, UK , Vivek is presently working as a Digital Transformation Leader at Tech Mahindra. He is leading digital initiatives in Tech Mahindra mostly focusing around Robotic Process Automation and Artificial Intelligence. He is helping customers to solve their business problems as well as innovate their business processes using digital transformation solutions. He also gets involved in Intelligent Automation assessment, planning, governance and execution using appropriate tools and technologies.

schedule 08:45AM ? 09:00AM Registration
schedule 09:00AM ? 09:15AM Workshop Overview
Nitesh Naveen, Partner & Managing Consultants - Digital Transformation, AI and RPA
schedule 09:15AM - 05:00PM Catapulting Your Automation Journey - Click Here for More Info
Vivek Prakash Surya, Practice Head, Tech Mahindra
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Name: 1.21 Gigawatts

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