My notes on some books I read on Machine Learning

Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow - Aurélien Geron [open notes]
Python Machine Learning - Sebastian Rashcka [open notes]
The Hundred-Page Machine Learning Book - Andriy Burkov [open notes]
Introduction to Machine Learning with Python: A Guide for Data Scientists - Andreas C. Müller and Sarah Guido [open notes]
Building Machine Learning Powered Applications: Going from Idea to Product - Emmanuel Ameisen [open notes]
Learning Spark: Lightning-Fast Data Analytics - Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee [open notes]
An Introduction to Statistical Learning - Gareth M. James, Daniela Witten, Trevor Hastie, Robert Tibshirani [open notes]
Machine Learning Engineering - Andriy Burkov [open notes]
Designing Machine Learning Systems - Chip Huyen [open notes]

Name		Name	Last commit message	Last commit date
Latest commit History 111 Commits
build-ml-app		build-ml-app
designing-ml-systems		designing-ml-systems
examples		examples
hands-on-ml		hands-on-ml
hundred-page-ml		hundred-page-ml
images		images
intro-ml-python		intro-ml-python
intro-statistical-learning		intro-statistical-learning
learning-spark		learning-spark
ml-engineering		ml-engineering
python-ml		python-ml
.gitignore		.gitignore
README.md		README.md

Provide feedback