Machine Learning

Past Presentations

The Move to AI: From HFT to Laplace Demon

The race for low latency data continues. 10 years ago, Flashboys were helping HFT make money with low-latency infrastructures. Today, hedge funds build AI brains pumping hundreds of sources of data in real-time, seeking ubiquity to build Laplace Demons.

Eric Horesnyi CEO @streamdata.io
Albert Bifet Associate Professor @Telecom ParisTech
The Internet of Things Might Have Less Internet Than We Thought?

While machine learning is traditionally associated with heavy duty power-hungry processors, it is beginning to look like the future of machine learning is on the edge. The ability to run trained networks “at the edge” nearer the data without access to the cloud — or in some...

Alasdair Allan Scientist/Maker/Hacker
Predictability In ML Applications

In the context of building predictive models, predictability is usually considered a blessing. After all – that is the goal: build the model that has the highest predictive performance. The rise of ‘big data’ has in fact vastly improved our ability to predict human behavior thanks to the...

Claudia Perlich Chief Scientist at Dstillery
Visual Intro to Machine Learning and Deep Learning

Break into machine learning with this gentle and intuitive journey through central concepts in machine learning -- from the most basic models up to the latest cutting edge deep learning models. This highly visual presentation will give you the mental map of ML prediction models and how...

Jay Alammar VC and Machine Learning Explainer @STVcapital
DSSTNE: Deep Learning at Scale

DSSTNE (Deep Sparse Scalable Tensor Network Engine) is a deep learning framework for working with large sparse data sets. It arose out of research into the use of deep learning for product recommendations after we realized existing frameworks were limited to a single GPU or data-parallel scaling...

Scott Le Grand Deep Learning Engineer @Teza (ex-Amazon, ex-NVidia)
Machine Learning Through Streaming at Lyft

Uses of Machine Learning are pervasive in today’s world. From recommendations systems to ads serving. In the world of ride sharing we use Machine Learning to make a lot of decisions in realtime, for example: supply/demand curves are used to get an accurate ETA(estimated time of arrival) and...

Sherin Thomas Senior Software Engineer @Lyft

Interviews

Peter Elger Co-Founder & CEO @fourtheorem

The Fast Track to AI with Javascript and Serverless

What is the work that you are doing today?

A lot of our work involves three threads. We're very active in serverless. And a lot of that is actually looking at legacy world challenged platforms and helping transform them into systems that can run in a serverless way. There's a lot of organizations that have realized that the economic operating model for cloud and...

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Carlos Garcia Ocado Smart Platform Fraud Team Lead Przemyslaw Pastuszka ML Engineer @Ocado

Real-Time Decisions Using ML on the Google Cloud Platform

What is the focus of your work today?

Carlos: The team is currently building the new ML-powered fraud application, to be used by fraud agents at Ocado and also other retailers using our Ocado Smart Platform. The team is currently focused on building the pipelines that allow us to integrate the real-time production systems with the “big data” stored in Google Cloud and...

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Michael Maibaum Chief Architect @SkyBet

Pragmatic Resiliency: Super 6 & Sky Bet Evolution

What is your talk about?

You go to a lot of conferences and you hear people from Google or Netflix talking about reactive architectures or the Simian army or whatever, and it all feels quite unattainable for a lot of people. It's like this big complicated thing, there is not much like those systems. And Sky Bet has changed quite a lot over the last few years....

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Jessica Yung Machine Learning blogger and entrepreneur, Self-Driving Car Engineer Scholar @nvidia

Understanding Deep Learning

Tell me a bit about your experience with deep learning.

I frequently use deep learning for a range of different things, very often with time series. Previously I worked in finance. We tried to predict different kinds of stock prices, bond prices and economic indicators. I also worked with self-driving cars. The inspiration for this talk was really very much based in what I was doing because...

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Sherin Thomas Senior Software Engineer @Lyft

Machine Learning Through Streaming at Lyft

What is the work you are doing today?

I work for a ride sharing company called Lyft. Our mission is to improve people's lives through the world's best transportation. For the last two and a half years, I have been working on the streaming platform team. In the ride sharing world, it is imperative to build the most recent state of the world and take decisions based...

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