This is my digital library.
It doesn’t follow a particular order, but the first one is my favorite and in my heart :-)
- The C Programming Language. Second Edition. Brian W. Kernighan, Dennis M. Ritchie
- C Programming, A Modern Approach. K.N. King
- Fundamentals of Software Architecture, An Engineering Approach. Mark Richards, Neal Ford
- Introduction to 64 Bit Intel Assembly Language Programming for Linux. Ray Seyfarth
- Fundamentals of Deep Learning, Designing Next-Generation Machine Intelligence Algorithms. Nithin Buduma, Nikhil Buduma, Joe Papa
- Deep Learning. Ian Goodfellow
- A Common-Sense Guide to Data Structures and Algorithms, Level Up Your Core Programming Skills. Jay Wengrow
- Introduction to Algorithms. Thomas H. Cormen
- Database System Concepts. Abraham Silberschatz
- Understanding and Using C Pointers. Richard Reese
- Practical Statistics for Data Scientists. Peter Bruce, Andrew Bruce
- Computer Networking, A Top-Down Approach. Kurose
- The Elements of Statistical Learning, Data Mining, Inference, and Prediction. Trevor Hastie, Robert Tibshirani, Jerome Friedman
- Exploratory Data Analysis. John W. Tukey
- The Hundred-Page Machine Learning Book. Andriy Burkov
- Machine Learning Design Patterns, Solution to Common Challenges in Data Preparation, Model Building, and MLOps.
- Linux Pocket Guide, Essential Commands. Daniel J. Barrett
- The DevOps Handbook. Gene Kim et al.
- Cloud Native DevOps with Kubernetes. Building, Deploying, and Scaling Modern Applications in the Cloud. Justin Domingus, John Arundel