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06 November, 2020
Global Online Live Conference
(All time mentioned in New York Time Zone)

World Machine Learning Summit- North America

Theme : Data Science, Deep Learning, and Algorithms
06 November, 2020
Global Online Live Conference
(All time mentioned in New York Time Zone)

World Machine Learning Summit- North America

Theme : Data Science, Deep Learning, and Algorithms
06 November, 2020
Global Online Live Conference
(All time mentioned in New York Time Zone)

World Machine Learning Summit- North America

Theme : Data Science, Deep Learning, and Algorithms
Ways to convince Your Boss Ways to Save

Briefly Know About This Event

We are very excited to announce our 3rd edition of World Machine Learning Summit- North America-2020, being organized by 1point21GWs, stay ahead with us!

World Machine Learning Summit- North America is a 1 day conference on 06 November, 2020. This is a Program being curated based on guidelines from industry experts, with a target of about 500+ delegates.

Theme of the Conference:
The Summit will be on what are the key challenges to improve your Machine Learning strategy and Implementation, Tools, API and Frameworks, Application/Use case & Deep Learning.

  • Track 1 : Data Science
  • Track 2 : Analytics
  • Track 3 : Machine Learning
  • Track 4 : Languages, Libraries, Platforms & Tools







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

  • 40+

    Global Speakers

  • 40+

    Topics

  • 4

    Tracks

  • 4

    Workshops

Conference Schedule (November 06, 2020)

Track 1 : Data Science

Timezones : New York - 11:00AM, Seattle - 08:00AM, Denver - 09:00AM, Boston - 11:00AM, Toronto - 11:00AM, Chicago - 10:00AM

X Topic Abstract

In the session i will explain practical examples of how we do it in our organisation.

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.

schedule 10:45AM - 11:00AM Registration / Conference Overview
Nitesh Naveen, Founder, 1.21GWS
speaker
11:00AM - 11:30AM Building a data science centre of excellence- Click Here for More Info
Wessel Oosthuizen, Associate Director – AI Lead, Deloitte, Johannesburg
speaker
11:30AM - 12:00PM Artificial Intelligence to attain global sustainable development goals
Srujana Kaddevarmuth, Board member of United Nations Association
speaker
12:00PM - 12:30PM Data ethics, bias and best Practices
schedule 12:30PM - 01:30PM Break
Schedule 01:30PM - 02:00PM Recommendation engines
speaker 02:00PM - 02:30PM Data Discovery in Data Lakes
speaker 02:30PM - 03:00PM How being an information generation is driving Big Data and business change
schedule 03:00PM - 03:30PM Break
speaker 03:30PM - 04:00PM Applications of Artificial Intelligence for the Mature and Emerging Sectors
speaker 04:00PM - 04:30PM Framework, best practices and strategies for data ingestion, transformation and storage in the new AI/ML world
schedule 04:30PM - 05:30PM Finals : ML Olympiad - North America

Conference Schedule (November 06, 2020)

Track 2 : Analytics

Timezones : New York - 11:00AM, Seattle - 08:00AM, Denver - 09:00AM, Boston - 11:00AM, Toronto - 11:00AM, Chicago - 10:00AM

X Topic Abstract

The talk will focus on how implementing Robotic Process Automation(RPA) in the sector of finance is optimizing the manual operational processes, while offering effective protection against financial cyber threats. We'll then talk about how RPA is also beneficial for data management and is disrupting financial services with infused Artificial Intelligence(AI).

X Topic Abstract

Key takeaways from my session:
In this session, we will walk through the process of succeeding in the analytics journey. We will examine the best approach to building a corporate analytics function and a high performing analytics team. We will describe and discuss the Artisanal and Modular approaches to hiring and building a team. We will also examine how to evolve from the Artisanal and/or Modular model to a Hybrid model. We will examine how to manage a high performing analytics team to deliver analytical models and applications that are implemented and used in daily operations to improve organizational efficiency and effectiveness. Be ready to ask questions, this will be an interactive and open discussion.
Format can be any of the below:
· 45 minutes Presentation with real life examples

Speaker Profile

John is an international technology executive with over 30 years of experience in the business intelligence and advanced analytics fields. Currently, John is responsible for the global Advanced Analytics & Artificial Intelligence team and efforts at CSL.
Prior to CSL, John was an Executive Partner at Gartner, where he was management consultant to market leading companies in the areas of digital transformation, data monetization and advanced analytics. Before Gartner, John was responsible for the advanced analytics business unit of the Dell Software Group.
John is the author of the new book – Analytics Teams: Leveraging analytics and artificial intelligence for business improvement. The book was published in June 2020 and outlines how to hire and manage high performance advanced analytics teams. The book outlines how to engage with executives and senior managers. How to select and undertake analytics projects that change and improve how a business operates.
John is co-author of the bestselling book – Analytics: How to win with Intelligence, which debuted on Amazon as the #1 new book in Analytics in 2017. Analytics is a book that guides non-technical executives through the journey of creating an analytics function, funding initiatives and driving change in business operations through data and applied analytical applications.
Mr. Thompson’s technology expertise includes all aspects of advanced analytics and information management including – descriptive, predictive and prescriptive analytics, artificial intelligence, analytical applications, deep learning, cognitive computing, big data, data warehousing, business intelligence systems, and high performance computing.
One of John’s primary areas of focus and interest has been to create innovative technologies to increase the value derived by organizations around the world.
John has built start-up organizations from the ground up and he has reengineered business units of Fortune 500 firms to reach their potential. He has directly managed and run - sales, marketing, consulting, support and product development organizations.
He is a technology leader with expertise and experience spanning all operational areas with a focus on strategy, product innovation, growth and efficient execution.
Thompson holds a Bachelor of Science degree in Computer Science from Ferris State University and a MBA in Marketing from DePaul University.

X Topic Abstract

Understanding the challenges in applying AI at scale for online decision making, and the opportunities for improved products and architectures that lie in solving them.

There is a ton of resources available on how to train machine-learned models, but how do you make use of them in real solutions once they are trained? If you need to evaluate models over big data sets and scale to thousands or millions of evaluations per second, such as in online recommender and ad systems, this is a very hard challenge. A few of the few biggest internet companies in the world has proprietary solutions for solving this problem, but until recently it has been out of reach for anybody else.

This talk will explain why this is a hard problem, show some of the things that become possible once a solution is available, and describe how we use the open source Vespa.ai platform to solve this problem in some real use cases including the world's third largest ad network.

Speaker Profile

Jon Bratseth is a VP architect in the Big Data and AI group of Verizon Media, and the architect and one of the main contributors to Vespa.ai, the open big data serving engine. Jon has 20 years experience as architect and programmer on large distributed systems, and a frequent public speaker. He has a master in computer science from the Norwegian University of Science and Technology.

schedule 10:45AM - 11:00AM Registration / Conference Overview
Nitesh Naveen, Founder, 1.21GWS
speaker
11:00AM - 11:30AM RPA and AI disrupting the Financial Industry’- Click Here for More Info
Vinnie Saini, Director, Enterprise Data & Analytics Architecture, Scotiabank
speaker
11:30AM - 12:00PM Building Analytics Teams: How to attract, hire and manage a high performance analytics team- Click Here for More Info
John K. Thompson, Global Head of Advanced Analytics & AI, CSL Behring
speaker
12:00PM - 12:30PM Big data serving: The last frontier. Processing and inference at scale in real time- Click Here for More Info
Jon Bratseth, VP Architect, Verizon Media
schedule 12:30PM - 01:30PM Break
Schedule 01:30PM - 02:00PM Data to Insights to Decisions In BFSI
speaker 02:00PM - 02:30PM Feature Based Opinion Mining
speaker 02:30PM - 03:00PM Industry 4.0 – Pain vs gain. Why everyone should understand this paradigm?
schedule 03:00PM - 03:30PM Break
speaker 03:30PM - 04:00PM Democratization of AI with Augmented Analytics
speaker 04:00PM - 04:30PM How are Best-in-Class Organizations Institutionalizing Analytics?
schedule 04:30PM - 05:30PM Finals : ML Olympiad - North America

Conference Schedule (November 06, 2020)

Track 3 : Machine Learning

Timezones : New York - 11:00AM, Seattle - 08:00AM, Denver - 09:00AM, Boston - 11:00AM, Toronto - 11:00AM, Chicago - 10:00AM

X Topic Abstract

Bert and other deep learning technologies need to be adapted to work for long document classification

Speaker Profile

Irina Matveeva is Chief of Data Science and AI at Reveal Data, an eDiscovery company based in Chicago. She is also Adjunct Professor at the Illinois Institute of Technology where she teaches Data Mining. Matveeva earned her PhD in Computer Science from the University of Chicago and her professional expertise includes Natural Language and Machine Learning technologies. Matveeva frequently presents on the subject of AI and NLP. She has been a volunteer mentor for the Data Science for Social Good fellowship.

schedule 10:45AM - 11:00AM Registration / Conference Overview
Nitesh Naveen, Founder, 1.21GWS
speaker
11:00AM - 11:30AM NLP and Deep Learning for long documents- Click Here for More Info
Irina Matveeva, Chief of Data Science and AI, Reveal Data & Professor at Illinois Institute of Technology
speaker
11:30AM - 12:00PM Doing More with Less: Building Machine Learning Solutions without Large Labeled Datasets
speaker
12:00PM - 12:30PM Tools demo: TensorFlow, cognitive cloud services, APIs etc for Java, C# and JavaScript.
schedule 12:30PM - 01:30PM Break
Schedule 01:30PM - 02:00PM Towards a Convenient ML Infra
speaker 02:00PM - 02:30PM Applying Machine Learning Online at Scale
speaker 02:30PM - 03:00PM Artificial Intelligence: Miracle or Menace
schedule 03:00PM - 03:30PM Break
speaker 03:30PM - 04:00PM Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning
speaker 04:00PM - 04:30PM Recommender Systems
schedule 04:30PM - 05:30PM Finals : ML Olympiad - North America

Conference Schedule (November 06, 2020)

Track 4 : Languages, Libraries, Platforms & Tools

Timezones : New York - 11:00AM, Seattle - 08:00AM, Denver - 09:00AM, Boston - 11:00AM, Toronto - 11:00AM, Chicago - 10:00AM

schedule 10:45AM - 11:00AM Registration / Conference Overview
Nitesh Naveen, Founder, 1.21GWS
speaker
11:00AM - 11:30AM Python
speaker
11:30AM - 12:00PM Scala
speaker
12:00PM - 12:30PM SAS
schedule 12:30PM - 01:30PM Break
Schedule 01:30PM - 02:00PM Julia
speaker 02:00PM - 02:30PM Pig/Hive
speaker 02:30PM - 03:00PM Tensorflow, Keras, PyTorch, Caffe
schedule 03:00PM - 03:30PM Break
speaker 03:30PM - 04:00PM Scikit-learn, Theano, Shogun, Pylearn2, XGBoost
speaker 04:00PM - 04:30PM Apache Spark, MLlib, Streaming
schedule 04:30PM - 05:30PM Finals : ML Olympiad - North America

Workshop 1 : Machine Learning 101++ Using Python

X Workshop Overview

Machine learning is often hyped, but how does it work? We will show you hands-on how you can do data inspection, prediction, build a simple recommender system, and so on.

Content & Process
Using realistic datasets and partially programmed code we will make you accustomed to machine learning concepts such as regression, classification, over-fitting, cross-validation and many more. This tutorial is accessible for anyone with some basic Python knowledge who’s eager to learn the core concepts of machine learning.

Audience & Requirements
Anybody who can write some code in whatever programming language should be able to follow the workshop. We make use of an iPython/Jupyter Notebook running on a dedicated server, so nothing but a laptop with an internet connection is required to participate.

schedule 10:45AM - 11:00AM Registration / Workshop Overview
speaker
11:00AM - 05:00PM Machine Learning 101++ Using Python

Workshop 2 : Essential Workshop to Exploratory Data Analysis and Feature Engineering

X Workshop Overview

Agenda:
Primary data analysis and Preprocessing
Exploratory Data Analysis
Feature Engineering
Machine Learning model training and evaluation

Audience & Requirements
The workshop requires participants to have a basic knowledge of Python and Machine Learning.

Requirement:
If you do not have any coding experience you are still welcome to join us to get a sense of how much effort is invested to develop a machine learning project.

Also, all the solutions will be provided during the workshop.

schedule 10:45AM - 11:00AM Registration / Workshop Overview
speaker
11:00AM - 05:00PM Essential Workshop to Exploratory Data Analysis and Feature Engineering

Workshop 3 : Machine learning from scratch in TensorFlow

X Workshop Overview

Schedule
Introduction to TensorFlow
Iterative algorithms
Machine learning
Basic neural networks

schedule 10:45AM - 11:00AM Registration / Workshop Overview
speaker
11:00AM - 05:00PM Machine learning from scratch in TensorFlow

Workshop 4 : Data wrangling with Python

X Workshop Overview

Outline
Clean and investigate numerical and textual datasets
Create and evaluate predictive models
Visualize results and derive insights from data

schedule 10:45AM - 11:00AM Registration / Workshop Overview
speaker
11:00AM - 05:00PM Data wrangling with Python

Register Your Attendance At Conference 2020

Any Question? Call: +1 908 444 0221

Ticket Price & Plan (For Conference)

(Per Participant)

Standard Price

USD 100

Till 06 November, 2020


Ticket Price & Plan (For Workshops)

(Per Participant)

Any One Workshop

USD 250

Till 06 November, 2020

Any two Workshops

USD 400

Till 06 November, 2020

Any three Workshops

USD 600

Till 06 November, 2020

All four Workshops

USD 700

Till 06 November, 2020


Our Sponsors

Use this opportunity to improve the visibility of your organization

Instant Sponsorship :


Avail instant sponsorship at just USD 200


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, naveen@1point21gws.info



Supporting Partner

Our Past Sponsors

Platinum Sponsor

Bronze Sponsors

Media Partner



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