machine learning

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?

DevNews #69 – Google Machine Learning Becomes Sentient – or does it just love shredders?

In this episode, Joel warns us that the machines have started to learn on their own – and that maybe they can tell shredders apart from trashcans… Also, a great TechCrunch article on how you can now build dynamic grids of compute servers using Mesos and have them automatically bootstrapped and configured by Docker. We talk about CoreOS, which is a small linux distro for beginning machine configurations, the Genymotion android VM that everyone was talking about at AnDevCon2013, and more.

DevNews #66 – RESTful tutorials, CAPCHAs and Machine Learning, a million to win a hackathon and more…

We talk about Newton – a pure Javascript Physics engine AI Startup says it has defeated captchas Got a great mobile app idea? You can win $1M in the SalesForce hackathon Elixir – a “groovy” for Erlang? We talk about JBoss Forge