Table of Contents
This page is dedicated to random things I would like to share.
👨💻 Self-educational approach
An efficient way to learn is to get few solid references and go through chapter by chapter to get a good understanding of the subject. After building foundations we can discover specific topics and expand our knowledge.
Hereunder my reading list for ML field.
- “Pattern Recognition and Machine Learning” (PRML) by Christopher Bishop - Download here
The “Deep Learning Book” by Ian Goodfellow, Yoshua Benign and Aaron Courville is a great detailed introduction to Deep Learning - Available online
For longer reads:
“Machine Learning A Probabilistic Perspective” by Kevin Murphy
“The Elements of Statistical Learning” by Hastie, Tibshirani and Friedman
It is also important to complement this with online courses that may help you dig deeper in certain fields (NLP, RL, Vision, Decision Making…) depending on your interests.
Reading references is an important step. But in the field of Machine Learning, experimenting with real data and coding is necessary for a better understanding. Here is a list to start with, they contain a lot of real world examples.
- Basic ML: Homemade ML repo and ML Algorithms repo
- Machine Learning From Scratch
- PyTorch Tutorials
- Google CodeLabs
Some blogs that worth looking at from time to time.
- The morning Paper: https://blog.acolyer.org/
- GroundAI: https://www.groundai.com/
- InfoQ: https://www.infoq.com/ai-ml-data-eng/
- Distill: https://distill.pub/
🔭 Research papers
⚛️ Atom is my go to editor (with Hydrogen and platformio-ide-teminal packages)
🐙 Gitkraken an amazing Git GUI Client.
📝 Trello and Github project boards for to-do lists.
💫 Machine Learning workspace
🖥 The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is very simple and convenient for ML experiments and development.
🐳 Docker to create customized containers for specific projects.
📚 Non-technical Books
Short list of a few of my favorite books.
- Sapiens: A Brief History of Humankind by Yuval Harari
- The Black Swan: The Impact of the Highly Improbable by Nassim Nicholas Taleb
- Homo Deus: A Brief History of Tomorrow by Yuval Harari
- Les jeux sont faits, Jean-Paul Sartre
- Voyage au bout de la nuit, Céline
- Les particules élémentaires, Michel Houellebecq
- The Grapes of Wrath, John Steinbeck