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December 03, 2021

Data Lake, Analytics & Machine Learning Summit - North America

Global Online Live Conference
All time mentioned in Eastern Time (New York / Atlanta / Toronto) zone

December 03, 2021

Data Lake, Analytics & Machine Learning Summit - North America

Global Online Live Conference
All time mentioned in Eastern Time (New York / Atlanta / Toronto) zone

December 03, 2021

Data Lake, Analytics & Machine Learning Summit - North America

Global Online Live Conference
All time mentioned in Eastern Time (New York / Atlanta / Toronto) zone

Ways to convince Your Boss Ways to Save

Briefly Know About This Event

Our hearts and thoughts remain with those affected by the COVID-19 outbreak worldwide. In the past months,1point21GWS has been organizing conferences on Virtual platform.

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 "deep" in "deep learning" refers to the number of layers through which the data is transformed. Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to its original goals. In deep learning, each level learns to transform its input data into a slightly more abstract and composite representation.

Agenda: December 03 , 2021
Track 1 : Tools, APIs & Frameworks
Track 2 : Applications/Use Case

  • 20+

    Global Speakers

  • 20+


  • 2


  • 1

    Day Conference

Conference Schedule (December 03, 2021)

Track 1 : Tools, APIs & Frameworks
Track 2 : Applications/Use Case

( All time mentioned in New York timezone )

Timezones : New York - 08:30AM, Seattle - 05:30AM, Denver - 06:30AM, Boston - 08:30AM, Toronto - 08:30AM, Chicago - 07:30AM
X Topic Abstract

The field of natural language processing is advancing faster than ever. Neural network based architectures and massive quantities of unstructured text data are consistently bringing state of the art results on tasks like question answering, summarization, text generation, and translation. However, this increased performance comes at a cost in terms of model size. Models like GPT-3, MegatronLM, and BERT contain hundreds of millions to billions of parameters. From a deployment and inference perspective, this makes leveraging them computationally expensive in practice. In this talk we will discuss knowledge distillation, a teacher-student paradigm that can allow us to compress these massive pre-trained models into similarly performing models with a drastically smaller model footprint.

Speaker Profile

Adam Lieberman is the Head of Artificial Intelligence & Machine Learning at Finastra. Leveraging a background in mathematics and computer science, he is responsible for the application of cutting-edge Machine Learning research and development to innovation efforts designed for the specific needs of the financial services industry. He leads Finastra’s data science teams, who focus on using the latest emerging technologies to conceptualize and rapidly iterate ideas, and turn proofs-of-concept into production-grade products and services, across Finastra's broad and deep financial technology portfolio.

X Topic Abstract

This talk will introduce how deep learning has been used in several use cases within the pharmaceutical space. These use cases include:
Identification of abnormal patterns for drug safety
Characterization of phenotypes in cell-based imaging
Classifying protein crystallization results

Speaker Profile

Peter Henstock is the Machine Learning & AI Lead at Pfizer. His work has focused at the intersection of AI, visualization, statistics and software engineering applied mostly to drug discovery but more recently to clinical trials. Peter holds a PhD in Artificial Intelligence from Purdue University along with 6 Master’s degrees. He was recognized as being among the top 12 leaders in AI and Pharma globally by the Deep Knowledge Analytics group. He also currently teaches graduate AI, Software Engineering, and Computer Vision courses at Harvard.

X Topic Abstract

The newest industry disruption is the Low-Code/No-Code (LCNC) development aims to empower business users to rapidly develop codeless applications to meet their needs. The distinction between tools that were thought to be simple enough for citizen developers and powerful enough for professional development teams are disappearing. In a true IT democratization process, citizen development is helping accelerate digitization of processes at an unprecedented rate. Through real-world examples, this talk aims to highlight the LCNC trend and how it is helping with Analytics and BI. Talk also provides constructive approaches which help IT / engineering teams embrace citizen developers while eliminating the historical points of friction from “shadow IT” work.

Speaker Profile

Garima V. Sharma is a senior engineering leader at Microsoft. She is a seasoned Tech professional, keynote speaker, STEM champion, technical blogger and proponent of diversity and inclusion. She runs a global team of data engineers and scientists focussed on building world-class analytics and BI solutions and next-gen AI applications. Garima has a passion for technology and has worked in progressive companies on Cloud Computing, Big Data & Artificial Intelligence solutions. She has helped shape science and technology for mission critical software, reliability in operations and re-design of architecture all geared towards advancements in medicine, security, cloud technologies and bottom line savings for the client businesses. An enthusiastic technology and STEM blogger, she brings together her passion for tech and diversity in her professional and personal endeavors.

X Topic Abstract

Definition Purpose of Strageic planning
Current AI Use in Marketing and Financial Management
Steps in SP
Data types in SP
Data sources in SP
Datawarehouse vs Data Lake
Problems to be addresses
Our Solutions
A video on Animated description on how we do

X Topic Abstract

Learned experience on how to:
Manage and process large quantities of data
Selecting the optimal and efficient training algorithms
Deploying and Monitoring Large-scale-models
MLOps and its best practices

Speaker Profile

Gayathri is a Senior Technology Executive/Chief Architect with 17+ years of IT experience in designing and engineering solutions for Enterprises at scale. This includes several technology transformation programs, process improvements via automation, solutions using Next Gen Technologies. Currently focused on design and development of an End-to-End Data solution platform that focuses in providing intelligent insights from varied unstructured data sources. Solution includes various domain specific AI/ML models using Vision intelligence, Text intelligence and Public Intelligence Frameworks/API’s.

schedule 08:30AM - 09:00AM 08:30AM - 08:50AM : Login / Registration
08:50AM - 09:00AM : Conference Overview
Abhilasha Sinha, Director- Summits, 1.21GWS
09:00AM - 09:40AM Keynote

schedule 09:40AM - 10:20AM Break
10:20AM - 11:00AM Track 1 : Knowledge Distillation - Click Here for More Info
Adam Lieberman, Head of Artificial Intelligence & Machine Learning, Finastra
Track 2 : Recommender Systems
11:00AM - 11:40AM Track 1 : Applying deep learning image understanding to drug discovery - Click Here for More Info
Peter Henstock, ML software Consultant, Harvard LecturerPfizer
Track 2 : Chat Bots & Virtual Agents
11:40AM - 12:20PM Track 1 : Democratization of data with No Code/Low Code Movement - Click Here for More Info
Garima V. Sharma, Senior Director, Data Engineering and Applied AIMicrosoft
Track 2 : AI-Driven Strategic Planning - Click Here for More Info
George B Moseley, Lecturer in Health Law and Management, Harvard School of Public Health (Boston), Visiting Professor, Strathmore Business School (Nairobi)
12:20PM - 01:00PM Track 1 : Towards a Convenient ML Infra

Track 2 : How to scale ML Projects - Lessons from Learned Experience - Click Here for More Info
Gayathri NVS, Associate Vice President, Straive
schedule 01:00PM - 02:00PM Break
speaker 02:00PM - 02:40PM Track 1 : Image & Object Recognition

Track 2 : Automatic Translation & Caption Generation
02:40PM - 03:20PM Track 1 : Applying Machine Learning Online at Scale

Track 2 : Visual Inspection & Action Recognition
schedule 03:20PM - 04:00PM Break
speaker 04:00PM - 04:40PM Track 1 : Artificial Intelligence: Miracle or Menace

Track 2 : Entity Recognition & Text Extraction
speaker 04:40PM - 05:20PM Track 1 : Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning

Track 2 : Speech, Gesture & Character Recognition

Conference Ticket Price & Plan

Early Bird

USD 249

Till November 03, 2021

Group of 3 or more

USD 299

Till December 03, 2021

Individual (Standard Price)

USD 399

Till December 03, 2021

Our Sponsors

Use this opportunity to improve the visibility of your organization

Instant Sponsorship :

Instant Sponsorship Includes :

Branding of your company as Bronze Sponsor - Company's Logo on the event page with cross link to your website. One delegate pass.
10% discount on registration fee for any more delegate from your organization.
Introduction Via Email.
Full day attendance 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

nitesh@1point21gws.info, abhilasha@1point21gws.info

Our Past Sponsors


• 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
Understand the state of development of Machine learning by exchanges, clearing houses, central counter parties and payment systems, and what it means for you.
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.
Best practices while attending online conference:
Login to your system with the login detail 10 minutes prior to the start time
Should be connected to a good network to avoid interruptions.
Should be at a quiet place while taking your session.
Ensure all other windows are closed and no application is running. This will ensure good audio and video quality
Mute yourself if not expected to speak
Do ask the question via chat box to keep the session lively. You can Ask questions
Yes, all conference attendees must register in advance to attend the event.

Register Your Attendance At Conference 2021

Any Question? Call: +91 9810667556