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London Meetup: Deep Dive into TensorFlow #17
REGISTRATION: Welcome to a very special TensorFlow London event, hosted together with London Artificial Intelligence Meetup. This event will be held at Printworks, SE16 (as part of AI Tech World Conference). PLEASE NOTE: You will be required to have a Conference Pass to enter the Printworks venue and make sure you claim your FREE EXPO PASS (you can find full details at the registration page/ link above). Agenda: 17:45 Doors open. Food networking and drinks 18:15 Opening Remarks 18:20 Lighting Talk: Data Science with Docker by Laura Mitchell 18:25 Are we alone? How NASA Frontier Development Lab scientists use AI to find evidence of life by Frank Soboczenski 18:50 Practical Reinforcement Learning with OpenAI by Leonardo De Marchi 19:05 Ultra portable Deep Learning with Tensorflow.js by Zack Akil 19.30 Wrap-up _________________________________________________________ DETAILED AGENDA: Lightning talk: Data Science With Docker Speaker: Laura Mitchell, Senior Data Scientist at Badoo Abstract: This talk aims to demystify Docker and it will provide an overview of what all the fuss is about. You can expect to hear: use cases and how to leverage Docker in your work, particularly for deep learning projects. Talk #1 Title: Are we alone? How NASA Frontier Development Lab scientists use AI to find evidence of life Speaker: Frank Soboczenski Abstract: How can artificial intelligence help answer one of the most challenging and intriguing questions of our existence: Are we alone? This talk will focus on explaining the detection of habitable planets by using the first machine learning atmospheric retrieval framework for terrestrial exoplanets. This project involves NASA, Google Cloud, NVIDIA, Intel, IBM, Kx, SETI Institute and others. You can expect to hear about the NASA program, current research in the field, data structure/generation implementation with Google as a partner and a brief outline on the implementation. Bio: Frank is a computer scientist at King's College London as well as a NASA Globe STEM scientist and former NASA Space Apps Lead. His research is supported by NVIDIA and focuses on Deep-Learning and Natural-Language Processing. Frank has previously worked in areas such as Human-Computer Interaction, Real-Time Systems and Cyber-Security in cooperation with INRIA, Airbus, GCHQ as well as other law enforcement entities. Talk #2 Title: Practical Reinforcement Learning with OpenAI Speaker: Leonardo De Marchi, Lead Data Scientist in Badoo Abstract: Reinforcement Learning recently progressed as one of the best techniques for sequential decision making and control policies in the industry. DeepMind used RL to greatly reduce energy consumption in Google's data center. It is used to do text summarisation, autonomous driving, dialog systems, media advertisement and in finance by JPMorgan Chase. In this talk, Leonardo will present some of OpenAI research, including OpenAi’s Gym and some algorithms like Proximal Policy Optimization (PPO). Bio: Leonardo De Marchi holds a Master in Artificial intelligence and has worked as a Data Scientist in the sports world, with clients such as New York Knicks and Manchester United, and with large social networks, like Justgiving. He now works as Lead Data Scientist in Badoo Talk #3 Title: Ultra portable Deep Learning with Tensorflow.js Speaker: Zack Akil, Developer Advocate at Google Abstract: Traditional machine learning systems usually require some installation process when you want to run them on your own device, not anymore! Zack will be giving give an overview of TensorFlow.js, which allows you to be training and running ML models on your device by simply visiting a webpage. Bio: Zack is Developer advocate at Google and Central London Data Science Project Nights meetup organizer.

Printworks London

Surrey Quays Road · London SE16 7PJ

What we're about

Does TensorFlow have the potential to become the engine behind most successful consumer and industrial products of the next 10-20 years?

Absolutely! A much better question is how, and in what new ways, can we:

a) train more computers to teach themselves by sifting through massive amounts of data coming out of all sorts of places

b) make these computers available through an API to provide a high-quality answer to anyone who is in need.

Why? Because everyone in need deserves the right answer.

So.... why don't we standardize & democratize the field with and around TensorFlow, and help change the world!?

What. We are a local micro community of those interested in advancing their knowledge of TensorFlow, its use cases and applications.

How. Join our group for a regular dose of human interaction, conversations, smiles, food and drinks on all things TensorFlow:

• How-To's & Best Practices

• Tutorials

• Models

• Algorithms

• Multi-GPU Autoscaling in the cloud

• Tools & Integrations

We will learn how others solve some of the hard problems that exist in the world around us, and how others make predictive APIs and applications

Join the movement. Let’s change the world.

Because everyone in need deserves the right answer.

You are welcome:)

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