More Machine Learning

Introductory
Materials

• Generative AI glossary

• What is ML? IBM Intro

• Making Friends with Machine Learning by Cassie Kozyrkov, full course

• Lifecycle of an AI project by Cassie Kozyrkov

• What if we let AI do the thinking? by Cassie Kozyrkov

• To Explain or to Predict? by Galit Shmueli

• Uncertainty in Machine Learning by Jason Brownlee

• What are LLMs? by Kate Soule

• Data Scientist Cheat Sheet compilation by Samuel Jordan 

Upskill

Free:

• Structuring Machine Learning Projects

• Machine Learning Engineering fro Production (MLOps) by DeepLearning.AI

• Free Code Camp ML courses

• Full course of Making Friends with Machine Learning by Cassie Kozyrkov

• AI for Good from DeepLearning.AI

• Deep Learning Book 

• Bayesian Analysis Book and lecture notes from Columbia University's Andrew Gelman

• Statistical Learning with Sparsity

• Huggingface Open-Source AI Cookbook

• Fairness and Machine Learning book

• Machine Learning for Cyber Security

• Notes on Most Common ML Questions by Vinja AI

• Intro to Encoders and Decoders by huggingface 

Non-free:

• ML in Production course from Coursera is a good start for a refresher course on different aspects of developing a machine learning model that will be used as part of a larger system. Other courses from deeplearning.ai are also very helpful.

• AI for good course from Coursera raises interesting topics of integrating AI in human-centric projects.

• First Course In ML Book

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Quick Start ML Examples

• AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data 

• AutoGluon Fairness

• AutoTrain - Hugging Face

• Auto-sklearn

• Lazy Predict

• Lazy Text Predict

RUDI Extra ML

• Development for Data Scientists

• Implementation for Data Scientists