Machine Learning / Data Science notes

News

• mln.dev
• All AI News

Learning

• Virgilio - path for machine learning learning
• Awesome Machine Learning/Data Science repo -- all the links you could want and more
• Machine Learning Operations - curated list
• MIT Intro to Deep Learning course
• Intro to GeoML

Javascript/browser

• Very cool overview of ml5.js & p5.js, with a sample implementation

Reference

• Machine Learning in Python, Step-By-Step -- from the excellent machinelearningmastery.com site

• The Incredible PyTorch

• Neural Networks and Deep Learning - online book, CC-licensed, excellentdy

• ML Cheatsheet

• Picking the best model

Books

• A list of great ML books (many freely available)

Production

• Deep Learning in Production -- a curated set of links

TinyML

• Towards Data Science article
• Microsoft Bonsai -- classifier that can run on Arduino
• Edge Impulse -- neat service for making models easily & deploying to Arduino, Pi, etc

Repos

• Machine Learning Deliberate Practice -- great intro to one person's project to get better at ML

• AWS Sagemaker examples

• Microsoft Computer Vision Recipes

Data sets

• Practice ml with small, in-memory datasets from the UC ML Repository

Techniques

• Long short-term memory analysis with Keras and Python

Tools

• Cookiecutter data science - the DS equivalent of "rails new"
• GBDX Notebooks - Jupyter notebooks + Digital Globe imagery
• EasyImages - Library for easy image display in Jupyter notebooks (mentioned in this article about image segmentation)
• Boilerplate code for machine learning -- excellent

Image labelling

• Awesome data labelling resources
• MakeSense.ai -- cool online, open-source image labeller

Automated optimization

• H2O - Automated model optimization
• TPOT

Libraries

• Folium - Python + LeafletJS for maps

• Categorical Encoding - Scikit-Learn library

• Segmentation models for PyTorch

Engineering

• OPML Conference 2019 -- Usenix conference

Computing

• Intel for display, NVidia for computing

Projects

• Bird identification with Keras and CNNs Good overview of resources for bird identification