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Overview of the event

Machine Learning Day will be happening on 2nd February, 2019 in Delhi.

Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to "learn from data, without being explicitly programmed.

The Event “Machine Learning Day” is a Program being curated based on guidelines from industry experts. The theme of this conference is to emphasise on the industry best practices needed for Machine Learning to learn the latest in the Machine Learning domain.

Facts & Figures About The Event

7 Speakers
7 Topics
50 Tickets

Our Past Speakers

Srivatsan Santhanam

Sr Director


Awantik Das

Co-Founder | AI Speaker | Corporate Trainer

EdYoda, Zeke Labs

Muralidhar Sridhar

Vice President, Centre of Excellence AI and Machine Learning and Advisor

Prime Focus Technologies

Sachin Mudholkar

VP Technology

Relatas - Sales AI

Bharath Hemachandran

Principal Consultant


Siddheshwar Jain

Technology and Transformation Specialist

Formerly Oracle, SocGen and Fidelity

Usha Rengaraju

Sr Data Scientist, Polymath & Ambassador

neoEYED inc, AIMed

Chandra Bhanu Jha

Data Scientist, Author & Founder

American Express

Conference Schedule

Machine Learning Day (2nd February, 2019)

X Topic Abstract

In this talk, we will demonstrate that deep learning has a very strong connection to the psychology of human decision making. Several behavioural economists and psychologists have researched on the hidden parameters through which we learn and make decisions, especially under uncertainty. We will talk about few such important life decisions that go beyond choosing a movie or doing eCommence. These decisions are around choosing a job, a life partner and a house. At Info Edge, we use deep learning in different businesses of the company, where the businesses are a job-portal (India's largest), matrimony (aka dating) site and a real estate site.

Speaker Profile

Nitendra Rajput works as Executive Vice President and Head of Data Science at Info Edge where he defines and leads the data science work for various Info Edge businesses such as naukri, jeevansathi, 99acres. Prior to this, Nitendra was at IBM Research for 18 years, managing the mobile agenda for IBM Research in India.
Nitendra has authored over 80 publications at top international ACM and IEEE venues, owing to which he has been recognized as an ACM Distinguished Scientist and a senior IEEE Member. He has delivered several tutorials and conducted workshops in AI and speech areas at top ACM venues (MobileHCI, IUI, CSCW, CHI). With over 50 patents to his name, Nitendra was an IBM Master Inventor and was also an IBM Academy of Technology member. In 2012, he coauthored a book titled "Speech in Mobile and Pervasive Environments" that was published by John Wiley & Sons.

X Topic Abstract

In the current world of cloud computing, and availability of many high end AI libraries, the success of AI for an enterprise is highly dependent on its peripheral system to support the continuous data supply and feedback channel. My talk will focus on how the blockchain enables and integrate multiple parties to put together a trusted data ecosystem

X Topic Abstract

This talk will focus on the usage of machine learning techniques in algorithmic trading. Indeed, machine learning will automate the trading process but to find the suitable machine learning technique and to generate appropriate signal are not an easy task. The volatile behaviour of the market makes it difficult to predict the behaviour of the market. There are other factors also, which make this problem more difficult as well as interesting

Speaker Profile

Hemant Jalota is Machine Learning Researcher at DeepR Analytics. He focused on creating trading algorithms that remove human error from the process. His specific areas of expertise include portfolio management, modelling and simulation, machine-learning algorithms, operation research, and fuzzy set theory.
He holds a Doctor of Philosophy in Mathematics from the Indian Institute of Technology Mandi, and a Master of Science in Mathematics from DAV University, Jalandhar, India. He’s also held academic positions for four years.

X Topic Abstract

It goes without saying that Natural Language Processing, or NLP, is one of the most important and demanded technologies of the present day. You can find it everywhere as people communicate almost everything in language: it is present in web searches, advertisement, emails, customer service, language translation, summaries, etc.
The talk would cover how the NLP has evolved over time, 2-3 use cases where NLP has significantly added value to the critical business problems and a couple of Demos on NLP based solutions.

X Topic Abstract

This talk will introduce the audience to nitty-gritty of Reinforcement Learning. Unlike supervised learning, reinforcement learning does not require labelled training data, instead here the agent learns with its interaction from the environment. The talk will start with a discussion on different learning paradigms, focusing on how they differ from reinforcement learning. I will cover the two major RL methods: value-based methods and policy-based method s. In the end will leave audience with some open research problems in the field of DRL

Speaker Profile

Amita Kapoor is Associate Professor in the Department of Electronics, SRCASW, University of Delhi. She has been actively teaching neural networks for last twenty years. She did her Masters in Electronics in the year 1996, and her Ph.D. in the year 2011. During her Ph.D., she was awarded prestigious DAAD fellowship to pursue a part of her research work in Karlsruhe Institute of Technology, Karlsruhe, Germany. She had been awarded best Presentation Award at International Conference Photonics 2008 for her paper. She is a member of professional bodies like IEEE (Institute of Electrical and Electronics Engineers), INNS (International Neural Network Society), ACM (Association for Computing Machinery) and AAAI (Association for the Advancement of Artificial Intelligence). She has more than 40 publications in the international journals and conferences. She is co-author of two books "TensorFlow 1.x Deep Learning Cookbook" and "TensorFlow Machine Learning Projects" both by Packt Publishers. Her present research areas include Computer Vision, Natural Language Processing and Deep Reinforcement Learning.

X Topic Abstract

In the last few years, evolution of ML algos, specifically Deep Learning Algos (NN, RNN,and CNN models), have helped provide a new perspective of asking business question(s) and solving them, with much a lesser effort, to create value in various industries.
In the online content business domain, use cases around personalised content creation, content distribution, and content consumption have gained a lot of traction. The new tech has also helped optimise various parameters that has led to revenue maximisation in addition to value creation for the end user, thereby impacting the whole business cycle to reach new levels.
Ideas around social media content engagement pattern, UGC( User Generated Content) moderation, authentic content distribution patterns are at the core of ML based tech solutions. The talk would include 2-3 use cases around what has been done in TIL to solve critical business problems.

X Topic Abstract

Machine language augmented with deep & cognitive learning plays an indispensable role to make artificial intelligence more productive and realistic to drive business with intelligence. Today although we can see plethora of applications and analytics software driven by complex ML algorithms, yet we can strongly foresee a promising future wherein ML will play a critical role to drive the global business environment and will take at least 80% stake in real time decision making based on consumer and market behavior leveraging advanced predictive and prescriptive analytics. Today we are working on several complex algorithms and mathematical frameworks, to design ideas and solutions to bring disruptive technologies in the market, few of the disruptive ideas are as below:

• Self-tutored artificial neural networks
• Augmented robotics
• Humanoid chatbots
• Intelligent social sites
• Hallucinated augmented reality
• Intelligent auto-sensing & auto-healing cloud-based systems
• Internet of Intelligent Devices (I2D)
• ML in Healthcare and Lifesciences industry
• Augmented Knowledge Analytics (AKA)
During the conference session, each of the above ideas will be discussed in detail and will understand how these are leveraging advanced ML to bring values in the business and human life.

X Topic Abstract

Automated Machine Learning (AutoML) provides methods and processes to automate the end-to-end machine learning workflow towards solving real-world business problems. In traditional machine learning world, data scientist used to spend a considerable amount of time in Data wrangling, model selection and tuning, now with the advances of AutoML is provides methods and processes to make Machine Learning available for non-Machine Learning experts, to improve efficiency of Machine Learning and to accelerate research on Machine Learning. Automating the end-to-end process of applying machine learning offers the advantages of producing simpler solutions, faster creation of those solutions, and models that often outperform models that were designed by hand. Subtopics:
1. AutoML basics
2. Understanding of AutoML libraries like Auto-sklearn, AutoKeras (including TensorFlow)
3. Implementation of AutoML libraries

Our Sponsors

Use this opportunity to improve the visibility of your organization

Instant Sponsorship
Avail instant sponsorship at just USD 2000

Instant sponsorship includes
• Branding of your company as Bronze Sponsor – Company's Logo on the event page with cross link to your website.
• One Speaking Slot (45 min -non sales talk).
• 10% discount on registration fee for any delegate from your organization.
• Full day attendance at the event with lunch
• 1 x Roll up stand / Brochure distribution at the event
• Online Interview post of your company's senior executive at our media portal

For Silver, Gold Platinum & Titanium Sponsorship opportunites, please request for Sponsorship Brochure via email at contact@1point21gws.com, naveen@1point21gws.info

Our Speakers

Nitendra Rajput

Executive Vice President & Head of Data Science

Info Edge India Ltd.

Varun Sharma

Senior Manager

Sapient Consulting India

Dr. Hemant Jalota

Machine Learning Researcher

Deep R Analytics

Amita Kapoor

Associate Professor, Machine Learning Expert, Author

University of Delhi

Subhajit Bhattacharya

Program Manager- Innovation & Strategy Governance


Abhishek Nigam

General Manager

Times Internet

Jatin Gupta



Amit Gupta

Assistant Vice President - Engineering


Want to become Speaker Please register here Register

Our Pricing

Special Offer

Rs 7000 + GST

Till January 02
Group of three or more

Rs 7500 + GST

Till February 02
Early Bird

Rs 8000 + GST

Till January 02

Rs 10000 + GST

Till February 02

Our Testimonial


Who can attend Machine Learning Day in Delhi?

• 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

Why to attend Machine Learning Day in Delhi?

Understand the state of development of Machine learning by exchanges, clearing houses, central counter parties and payment systems, and what it means for you.

What will you learn about?

Detecting where underlying problems and frictions exist in your organisation that will be alleviated by Machine learning technologies. Using Machine learning as a tool for innovation across your organisation

Are there any prerequisites to attend this program?


Do I need to register for the event?

Yes, all conference attendees must register in advance to attend the event.

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