machine learning

Philly ETE 2019 – Leemay Nassery – Neural Networks IRL (In Real Life)

Abstract What exactly is a Neural Network? How do you go from experimenting with a deep learning model in the notebook of your choice to deploying your model to production? What is the secret sauce to a successful feature or platform that utilizes “AI” to accomplish the business goals or needs of your platform? And … Read More

Philly ETE 2019 – Anatoly Polinsky – Machine Learning: from ABCs to DEFs

Abstract I’d like to introduce you to this new, 60 year old, kid on the block: “Machine Learning”. Some math + some stats, but mostly “what”s, “why”s and “how”s of different problems it solves, and of course some code, since that’s what machines speak best. While we’ll ride along with mouthfuls such as “stochastic gradient … Read More

A Simple Neural Network to Classify Slack Messages

Over the past few weeks I’ve been experimenting with some basic machine learning. My task was to create a classifier for Slack messages. The application would be a slackbot that takes an input sentence and responds with whichever channel it believes the message should belong to. My bot only looks at three channels: #food, #fun, … Read More

Pink Noise in Neural Nets: A Brief Experiment

Disclaimer: Some basic exposure to machine learning is assumed.   Neural nets are on the rise, now that computing power and parallel data processing capabilities have reached the levels that allow them to shine. Recurrent neural nets, the more sophisticated kind that possess time dynamics, have achieved spectacular results in certain areas. Overfitting, however, has … Read More

PHLAI – Comcast's Artificial Intelligence Conference

I was lucky enough last week to attend PHLAI, a Comcast-sponsored conference on machine learning and artificial intelligence. The dreary weather did not dampen our spirits as practitioners and business stakeholders met to discuss one of the most important trends in our lifetime.

The O'Reilly AI Conference

I recently attended the O’Reilly AI Conference in New York where artificial intelligence practitioners showcased the impressive strides they’ve made so far in using AI for real-world applications

Philly ETE 2015 #26 – Soumith Chintala – The Deep Learning Revolution: Rethinking Machine Learning Pipelines

In the last decade, a class of machine learning algorithms popularly know as “deep learning” have produced state-of-the-art results on a wide variety of domains, including image recognition, speech recognition, natural language processing, genome sequencing, and financial data among others. What is deep learning? Why has it become so popular so quickly? How can one fit deep learning into existing pipelines?

ETE 2015 – Soumith Chintala – The deep learning revolution: rethinking machine learning pipelines

In the last decade, a class of machine learning algorithms popularly know as “deep learning” have produced state-of-the-art results on a wide variety of domains, including image recognition, speech recognition, natural language processing, genome sequencing, and financial data among others. What is deep learning? Why has it become so popular so quickly? How can one fit deep learning into existing pipelines?