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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 (21st February, 2019)
X Topic Abstract

Artificial Intelligence allows us to transform work and decision making in healthcare, transportation, retail, insurance, education and more. Every second, 2.5 billion emails are sent every second. Every year, 22 trillion messages are sent just on FB and WhatsApp. And even in complex fields like cancer research, 100,000 articles are written every year. In this age of data, there is an abundance of data but also an abundance of opportunity.
I believe businesses can only win in the age of data, if they train and leverage their data systems to get the most value out of them. In this presentation, I will show you three ways you can infuse AI into your business. I will walk you through how you can extract deep insights from both large and small data sets, to empower smarter business. I will show you how enterprise assistants and insight engines can distill structured and unstructured data through an intuitive NLP interface that makes it easy to query data to generate answers, insights, and trends.

Speaker profile

Angel was the CEO & Founder of Leaders Working, an EdTech company acquired by Bloomberg.

Following Leaders Working's acquisition, Angel worked in Venture Capital, investing and scaling SaaS and NextGen commerce companies before heading west to build and take to market products at Facebook and Google.

Today, Angel works at IBM Watson where he leverages AI technology to develop products that will deliver empathy at scale.

Learn more about Angel's journey at www.angelmontesdeoca.com

X Topic Abstract

Repeatability is the ability to conduct an experiment multiple times and get consistent results. Reproducibility is getting consistent results from different experimental designs. Showing the minute details of your work to a knowledgeable peer and getting his concurrence. How do we incorporate this into AI.

Scientific method consists of three concepts. Repeatability is the ability to conduct an experiment multiple times and get consistent results. Reproducibility is getting consistent results from different experimental designs. Showing the minute details of your work to a knowledgeable peer and getting his concurrence. How do we incorporate this into AI.

X Topic Abstract

Conversational AI is poised to become a standard layer of communication for SME's in the coming years. Larger corporations have already integrated chatbots and AI based voice recognition/response models into many of their customer facing points of interaction.
Thanks to NLP, large corporations have been able to initially field both sales and customer service inquiries with chatbots, thus getting consumers accustomed to expecting some form of AI interaction prior to speaking to an actual human, en masse.
In This Talk I Will Cover The Following:

1. How chatbot adoption has impacted consumer communication expectations
2. The importance of chatbots for SMEs
3. Use cases of chatbots in 2020 for sales and customer service
4. Ways SMEs can differentiate themselves with chatbot integrations

X Topic Abstract

Machine learning has been as a discipline has been the forte of experienced Data Scientists. There were only creators and consumers of Algorithms. But with growth and penetration of use cases combined with the scarcity of talent, the value chain is shifting closer and closer to the end users. While this trend may have its own set back and potential dangers, it is inevitable as ML becomes common place. Enterprises are rediscovering the Analytics organization to enable Citizen Data scientists to bring to scale to Machine Learning. This session looks at the trends, tools and frameworks to maintain the balance between usability and maintenance. ,

X Topic Abstract

Confusion exists everywhere, especially when we discuss artificial intelligence, machine learning and now deep learning is added to this list.

Deep learning is the next layer of applying intelligence on machines to help humans live better lives, ensure an exceptional experience when working with digital tools and even navigate unknown lands with just a smartphone and some apps on it.

Let us use this time to unpack machine learning, deep learning and what innovations have been applied and how they are benefiting healthcare, finance, retail, and other consumer needs.

The purpose of this session would be to explore the innovations in deep learning and machine learning. We will use methods such as analyzing the example solutions from each of these verticals to highlight the specific deep learning methods such as neural networks and speech recognition."

Speaker Profile

Rama Ravindranathan is an innovator and technologist, enthusiastically builds technology solutions to solve complex healthcare business problems. Her primary areas of focus are digital solutions that leverage ground breaking technology trends such as AI, Machine Learning and mobile development.

Rama Ravindranathan has been with Optum since 2010. Rama works with her business clients to understand their complex issues and creates technology strategy, roadmap to solve those problems in a simplistic way using Agile methodology. She is an innovation champion, who is responsible for promoting innovation through creative problem solving. Rama coaches innovators in the Optum Start-up Accelerator program.

Her professional experience includes working as a CRM implementation consultant in addition to extensive programming and development experience.

Rama has Bachelors in Computer Science and she is PMP certified from Project Management Institute. Rama was a certified Siebel Analytics consultant and implemented Siebel Analytics and Siebel marketing solutions. Rama is the innovation award recipient of UHG, where her innovative ideas were chosen as finalists among 1000 other ideas that were submitted to solve complex healthcare problems.

X Topic Abstract

Digital transformation is resulting in significant disruptive forces in the marketplace affecting talent landscape and emergence of technology solutions across HR to meet the needs. We'll discuss what those challenges are and how HR needs to respond to them with new skills, processes, AI infused products, creation of a digital platform and efforts around data quality and transparency.

Speaker Profile

Anshul is currently responsible for HR Data, AI and Offering Strategy at IBM and is infusing AI into all aspects of HR from recruiting, to developing, retaining and paying employees.

Previously he was a manager of a team of PhDs in Industries and Solutions Research at the IBM T J Watson Research Center. He is passionate about creating innovative customer experience analytics in partnership with the C-suite of clients.

Anshul was featured in Fortune CNN as IBMs Face of the Future and his work has been highlighted in the IBM investor briefing. He has been the Research Relationship Manager for GBS HR and co-lead of the Customer Insight and Marketing WW sub-strategy. For his leadership and contributions in these areas leading to measurable financial impact, he has received the IBM Corporate Technical Award, an Outstanding Innovation Award and three Outstanding Technical Achievement Awards.

His work has been accepted or published in Operations Research, Management Science, European Journal of Operations Research and Interfaces. He has served as an Adjunct Assistant Professor with New York University's Leonard N. Stern School of Business and a Guest Professor at the McCombs School of Business at the University of Texas at Austin. He received his PhD in Operations Management from New York University's Leonard N. Stern School of Business and a B.Tech. in Mechanical Engineering from the Indian Institute of Technology, Madras.

X Topic Abstract

Behavioral Science seeks to understand how humans process, absorb, and react to information. Machine learning is all set to revolutionize the application of behavioral science. With the application of both, we are able to test, deliver and evaluate behaviorally informed programs in the most effective and efficient way. This in term likely improves human decision-making.
My talk will consider pulling out examples on this context and show the power of hyper-personalization, nudge theory, etc where machine learning and behavioral science plays pivotal parts.



Our Sponsors

Use this opportunity to improve the visibility of your organization

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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


Angel Montesdeoca

Lead Product Manager

IBM


Arghya Mandal

Strategy, AI and Machine Learning practitioner

Deloitte


Srini Nachinarkiniar

Practice Director for Analytics and AI

Wipro


Vijay Nadendla

GLobal Head of Data Science

GLobal Head of Data Science


Bryan Hanley

Head of Artificial Intelligence Applications

Digital Mark 360


Rama (Ramanujapuram) Ravindranathan, PMP

Director of Product Management

UnitedHealth Group


Anshul Sheopuri

Vice President & CTO, Data, AI & Offering Strategy.

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 New York?

• 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 New York?

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.