GitHub

A repository for organizing my existing repositories and presenting a call to action for collaborators

Collaborators

Below are a list of projects that I am actively seeking collaboration on. Please feel free to check them out, contribute and ask questions about any of the below:

1. Bootstrapping (or perhaps better named: computational statistical inference in python). I am building out a bootstrapping library for data scientists. Very early stages.
2. Causal Inference python library. I would like to eventually build something like this out, but I have not even started. If interested please reach out.
3. YouTube. We are always interested in help with various parts of the channel (you can check out some of the videos and repos below)
4. Data science projects. I love to help out on new data sets and if all goes well we could make a Data Talks together.
5. Deep Learning Research. I have more ideas than I have time to implement, so if you know what you are doing (or have gone through my tutorial at A Bit of Deep Learning and Keras) I would love to work together
6. And as always I do Data Science Consulting for those with more serious data problems

Course Material

Below are repositories associated with courses that I teach. Feel free to reach out to me (or subscribe to me on twitter) if you would be interested in attending these or getting further information.

1. Deep Learning Workshop
2. Introduction to Machine Learning
3. Introduction to Data Science 2017
4. Introduction to Data Science 2016

Speaking Engagements

1. Planning on speaking at at the Big Data Conference about the real problems in data science
2. I spoke on representational learning at ODSC West (Video edit in progress)
3. I spoke on representational learning at Demystifying Artificial Intelligence

Contracts

A list of a couple of contractor projects that I have worked on:

1. I taught machine learning, data science and python to students at Salesforce with Develop Intelligence
2. Helped develop machine learning models for Autumn Wind Asset Management
3. Helped with due diligence on a prospective investment for Mubadala VC
4. I taught machine learning and deep learning to partners at G2 Venture Partners
5. I helped with model building and refinement at Onenigma

YouTube Material

Material that accompanies my YouTube channel videos. If you would be interested in helping out or joining the team please do reach out!

1. Statistical Inference
2. A Bit of Deep Learning and Keras: repo
3. A Bit of Data Science and Scikit Learn: repo
4. Data Talks: repo
5. Patsy Understanding the Weird Parts: repo
6. Seaborn Understanding the Weird Parts: repo
7. Meteor Maxims: repo

Lists and Information

Only one thing here now:

1. Deep Learning Paper Notes: A list of deep learning papers that I have read with some notes on 25% of them

Repo's I've Contributed To

1. Keras Resources
2. Scikit Learn
3. Tensorflow Models

Personal Projects

1. Validated Publish: a meteor.js library to define publications in a structured way, with mixins.
2. Robust Web Client: school project
3. Ipython and Stocks: very old school project

The Abandoned

Pretty much how it sounds. A list of abandoned personal projects that I might be interested in starting back up if there were somebody with enough of a spark to get them going again.

1. Deeds: a general attribution framework
2. Donelist: the name says it
3. Stances: a news site for polls and graphs