I’m a data scientist specializing in Machine Learning. The purpose of this page is to serve as a central point of reference for talks and blogs I write.
Machine Learning Ops, A collection of resources on how to facilitate Machine Learning Ops with GitHub.
fastai, I am a regular contributor to various fastai projects.
fastpages, an easy to use blogging platform for Jupyter Notebooks.
Issue Label Bot, A GitHub App powered by machine learning.
Links to associated github repos (and live demos if available) are located in blog articles.
Data Science Meets Devops: MLOps with Jupyter, Git, & Kubernetes: An end-to-end example of deploying a machine learning product using Jupyter, Papermill, Tekton, GitOps and Kubeflow. by Jeremy Lewi, Hamel_Husain, The Kubeflow Blog.
Introducing fastpages, An easy to use blogging platform with extra features for Jupyter Notebooks. by Jeremy Howard & Hamel Husain, GitHub Repo
GitHub Actions: Providing Data Scientists With New Superpowers by Jeremy Howard & Hamel Husain.
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search: by Miltiadis Allamanis, Marc Brockschmidt, Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit GitHub Repo
How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning. (Related: GitHub engineering blog article, Live demo)
JupyterCon 2020: “fastpages - A new, open source Jupyter notebook blogging system.”. Slides, Video - TBD
Gradient Descent by Weights & Biases: A discussion on Automated Machine Learning, CodeSearchNet, GitHub Actions and MLOps: Video
GitHub Universe 2019: “Machine Learning Ops With GitHub Actions & Kubernetes”. Video
Data Skeptic Interview, Jan 2018: “Semantic Search at Github”.