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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 (14th February, 2019)
X Topic Abstract

Data is fuel of all the industries and machine learning is the art of using patterns in data to make predictions. In this talk I will provide an overview of how data science and machine learning algorithms are reshaping the industries like healthcare, insurance and banking with real-time case studies.





X Topic Abstract

Tesla V100 GPU contains 640 Tensor Cores. Tensor Cores deliver up to 125 Tensor TFLOPS for training and inference applications. Automatic mixed-precision (AMP) is a way to take advantage of Tensor Cores high throughput computation in deep learning applications. AMP is supported in common deep learning frameworks like Pytorch and TensorFlow with NVIDIA's library. With two lines of code, you can enable AMP to accelerate your existing deep learning model training by 3x on average without loss of accuracy. AMP handles the model half-precision conversion, automatically loss scaling and master weight updating automatically under the hood. With a smaller memory footprint, you can train larger models with larger batch sizes. AMP is a popular technology that has been widely adopted in the deep learning community."

X Topic Abstract

Deep learning methods are extensively used in image processing, In my talk i will highlight some applications and present some use cases. I will give insights into the inner working for image recognition.

X Topic Abstract

The financial markets are always complex, volatile and unstable which forbids the accurate prediction of future prices. Moreover, financial markets produce large volumes of data at high frequency during each day. The presence of anomalies in voluminous data from multiple data sources may generate catastrophic decisions in market behavior. We propose a Deep Reinforcement Learning technique for detecting anomalies present in the historical daily trading information.

X Topic Abstract

The black box perception of machine learning models presents a barrier to their adoption for many investors. In this talk, I use a case study to many investors. In this talk, I use a case study to briefly discuss simple implementation of machine learning in the investment portfolios and explore ways to interpret and validate predictions.

X Topic Abstract

Strategic planning is a traditional business function which, when performed well, can give a business a powerful competitive advantage. Most businesses perform it poorly, leading to mediocre results and a loss of management confidence. We propose to use RPA, AI, and ML to automate the entire strategic planning process for every organization in the world. Customers will subscribe to a cloud-based system that they will access 24 hours a day and that will give them real-time reports and conclusions on their markets, customers, competitors, and environment.





X Topic Abstract

One of the uses of AI and machine learning is to make better decisions. Decision support entails causal models to predict the probable outcomes of the various choices in face of uncertainty. This talk will provide an overview of how to apply causal models with examples.



X Topic Abstract

Developing AI | ML and Deep Learning solutions are now more realistic given the vast amount of data, as well as the computer processing power that now exists. Given the interests by most organizations to gain valuable insights about their businesses using these new technologies, we've seen the development of new and exciting applications in marketing, supply chain, pricing, sales, and other disciplines. The flip side is that we're seeing more and more data breaches and exposure to sensitive customer data resulting in harm to Bands as well as potentially serious fines. This presentation provides some insights into strategies and solutions to get to "Know Your Data" while at the same time putting in place a foundation to your data strategy that will provide for governance.

Speaker Profile

Mr. Sieck is a technology executive and entrepreneur who has been involved with AI solutions starting early on with AI for Optical Character Recognition, to Computer Aided Design; and most recently for use in Predictive Analytics Use Cases across a number of verticals including Retail, CPG, FinTech, Healthcare, Financial Services, Insurance and others.

He is currently Director – Governance, Risk & Compliance | AI | Machine Learning solutions for Orion Governance that offers a disruptive new Data Governance enterprise software solution focused on technical lineage; for the first time allowing banks, insurers, retailers and other large enterprises to confidently ensure compliance with numerous regulations such as GDPR, BCBS-239, SOX, HIPAA, CCAR, Solvency II. It provides the clear, accurate visibility into corporate data drastically reducing operational risk.

Prior to Orion Governance, he was Director for Digital | Marketing Analytics at LatentView Analytics helping major F500 companies increase revenues and cut costs through the development and implementation of their Digital Transformation Strategies.

He was Director of Advanced Analytics for Hitachi and brought to market Hitachi’s first SaaS Solution platform that was an AI based solution called Live Insights for IT Operations that help give IT operations a 360-degree global view of their data center operations.

Prior to Hitachi, he was involved with a number of early stage VC financed technology companies as well as numerous turn-around entities that had successful exits.

He is an active member of the MIT Community and works with the MIT Venture Mentoring Services organization.

X Topic Abstract

Financial Scorecards are used widely in all financial organizations for different kinds of ratings. This talk will take you through the building and validation process of a financial scorecard using data.Financial Scorecards are used by banking organizations to judge the financial stability of their portfolio and take business decisions. These scorecards help in tracking and collections.

This talk is designed for audience to take them through the process of developing a scorecard . The talk will guide you through the EDA process and will demonstrate the different kind of visualizations that can enable better data understanding. We aim to cover step by step process of building a scorecard and Use of different Machine Learning algorithms to build a better scorecard by comparing the outputs of different algorithms. We will demonstrate 3 different Machine learning algorithms Random Forest , Support Vector Machine and Gradient Boosting and their outcomes while building this scorecard.





X Topic Abstract

One example is use of NLP and AI in rapid literature review for complex topics that in the past have required human review. Another example is using AI in operational aspects of clinical trials.

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

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Our Speakers


Nirav Shah

Founder

OnPoint Insights


Deepti Gupta

Author, Applied Analytics through case studies using SAS and R : Implementing Machine Learning Algorithms


Murray Cantor

Chief Scientist and Data Science Management Consultant

Aptage Consulting


Kevin Sieck

Director - Governance, Risk & Compliance | AI | Machine Learning

Orion


George B. Moseley

CEO & Professor

Strathmore University & AI Driven Strategies


Al Yazdani

Machine Learning and Data Analytics Manager

State Street


Niharika Karia

Data Scientist

Aspen Technology


Rajkumar Joghee Bhojan

Principal Consultant

Wipro Technologies


Chandni Valiathan

Director of Analytics

Kernal Biologics, Inc.


Yi Dong

Deep Learning Solutions Architect

NVIDIA

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 14, 2020
Individual(Early Bird)

USD 409

Till November 30, 2019
Individual (Standard)

USD 469

Till February 14, 2020


To Register Via Eventbrite

Our Testimonial

FAQs

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

• 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 Boston?

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.