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Overview of the event

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.



Facts & Figures About The Event

7 Speakers
7 Topics
50 Tickets

Conference Schedule

Machine learning and Deep Learning Day (21th February, 2020)

X Topic Abstract

Machine learning can be generally defined as a method or function which enable us to make decisions or learn unknown facts
based on the experience with respect to some class of tasks. This function enable us to solve problems which are difficult to be solved by mere problem solving or programming methods. Several different machine learning methods are used in different areas or problem sets. Basic methods are categorized as supervised machine learning methods and un-supervised machine learning methods. However the basic principle behind all the methods remain the same, that is to learn the facts and make decisions based on the unknown data. The scope of the machine learning methods is vast and varies with the problem definition and situation. I can try to explain some basic Machine learning methods, some research work done, applications, and my own projects.


X Topic Abstract

This talk will provide an overview of real-life industrial case studies on how machine learning/AI has provided significant value for business decision makers. Machine learning in various forms and facets have allowed businesses to extract vital inferences from the raw data, and enabled them take actions in the right direction. In particular, this talk will provide examples of how ML, natural language processing, and optimization algorithms have been applied in various fields such as Revenue Management, Personalized Recommendations, Supply Chain, and Operations to provide meaningful insights and generate value.


X Topic Abstract

This talk will acquaint the audience with practical and contemporary applications of machine learning. Starting from a context of human learning, the discussion moves onto how machines learn in similar ways, including models both machine supervised and unsupervised, and covering Bayesian inference. The "So what?" question of data science is addressed, and a description of how the academic discipline of Knowledge Management informs current machine learning and analysis.



Speaker profile

Andrew Paul Acosta earned a Masters of Business Administration with honors from Roosevelt University in Chicago, and is working on a PhD in Knowledge Management.

Andrew is the lead data scientist at Milesius Capital Resources LLC, a statistical consulting firm specializing in foreign currency trading, futures, swaps, fixed-income, and options, also offering expertise in financial risk management, and economic research in computing environments such as: R, SAS, MATLAB, C++, Python, and SQL.


X Topic Abstract

The talk will focus on how we extract insights (using deep learning and transformer models) from large volume of unstructured data and apply them to a variety of business domains, including: product competitive analysis, supply-chain disruptions, supplier monitoring and financial distress prediction.

Our Sponsors

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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

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Our Speakers


Sanket Chobe

Data Scientist

Wipro Ltd.


Anshul Agarwal

Senior Data Scientist

Trunk Club


Andrew Paul Acosta

Data Scientist

Milesius Capital Resources, LLC


Nick Kadochnikov

Data science Director

IBM

Want to become Speaker Please register here Register

Our Pricing

Group of three or more(Early Bird)

USD 300

Till November 30, 2019
Group of three or more(Standard)

USD 349

Till February 21, 2020
Individual(Early Bird)

USD 409

Till November 30, 2019
Individual (Standard)

USD 469

Till February 21, 2020


Our Testimonial

FAQs

Who can attend Machine learning and Deep Learning Day in Chicago?

• 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 and Deep Learning Day in Chicago?

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?

No

Do I need to register for the event?

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