Books
Free Books (they’re all high quality!)
- https://christophm.github.io/interpretable-ml-book/
- https://theeffectbook.net/index.html
- https://matheusfacure.github.io/python-causality-handbook/landing-page.html
- https://timeseriesreasoning.com/
- https://avehtari.github.io/ROS-Examples/
- https://mixtape.scunning.com/
- http://incompleteideas.net/book/the-book-2nd.html
- https://datascienceincontext.com/
- https://otexts.com/fpp2/
- https://leanpub.com/os
Ace Advanced ML Strategy
- The Only Book You Need to Ace Advanced Machine Learning Strategy
- Machine Learning Yearning - Andrew Ng
DevOps must-to-read list
Best Engineering Management Books
The Art of Business Value
Design Patterns
Continuous Delivery
Making work visible
Balaji Srinivasan Mentions
Data Structures and Algorithms
- Computer Science Distilled (Beginner friendly)
- Grokking Algorithms (Beginner friendly)
- Data Structures and Algorithms in Python (Beginner Friendly)
- Data Structures and Algorithms Made Easy (Intermediate)
- Introduction to Algorithms (Advanced)
- Algorithms 4th Edition (Advanced)
- Algorithm Design Manual (Advanced)
Software Design
- A Philosophy of Software Design
- Structure and Interpretation of Computer Programs
- How to Design Programs
- Grokking Simplicity - Taming complex software with functional thinking
- Architecture/Performance of Open-Source Applications, 500 lines or less
- Designing Data-Intensive Applications
- Fundamentals of Software Architecture: An Engineering Approach
- Software Architecture: The Hard Parts
- The Pragmatic Programmer: From Journeyman to Master
- Clean Code: A Handbook of Agile Software Craftsmanship
- Clean Architecture
- Architecture Patterns with Python: Enabling Test-Driven Development, Domain-Driven Design, and Event-Driven Microservices
- Designing Distributed Systems - Microsoft
- Designing Event-Driven Systems - Confluent
- Cracking the Low Level Design (LLD) Interview
Reinforcement Learning
- Bandit Algorithms - Tor Lattimore and Csaba Szepesvari
- Statistical Reinforcement Learning Modern Machine Learning Approaches
- Reinforcement Learning: An Introduction
- Foundations of Deep Reinforcement Learning Theory and Practice in Python
- Grokking Deep Reinforcement Learning
- Reinforcement Learning: Industrial Applications of Intelligent Agents
- Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
Deep Learning
MLOps
- Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
- Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
Recommender Systems
- Recommender Systems: The Textbook
- Practical Recommender Systems
- Recommendation Engines - The MIT Press Essential Knowledge
- AI-Powered Search
Architecture
- A Pattern Language: Towns, Buildings, Construction
- The Timeless Way of Building
- The Oregon Experiment
- A Theory of Architecture
- The Sympathy of Things: Ruskin and the Ecology of Design