I really enjoyed "Grocking Algorithms" by Aditya Bhargava because it takes a complex subject like algorithms and makes it accessible. Learning algorithms can be challenging, especially if you're trying to understand them from textbooks or research papers filled with mathematical proofs and equations. This book stands out because it avoids overwhelming the reader with such dry content.

Instead, the author uses illustrative and intuitive examples to explain every concept. These examples are easy to follow, especially if you're a visual learner. Whether you're new to data structures and algorithms or just refreshing your knowledge, this book excels at providing explanations without making you feel overwhelmed. After going through this book, you'll have a solid foundation to further explore the topic.

I highly recommend two books: "Clean Code" and "Clean Architecture," both authored by Robert Martin. These books have been recommended countless times, and for good reason. They encapsulate tried and tested software engineering best practices that every software engineer should be aware of.

While not every principle in these books may directly apply to modern engineering with distributed architectures, they remain invaluable when it comes to writing solid and maintainable code. These books provide numerous examples of good and bad code, as well as good and bad design, making it immensely helpful for anyone looking to improve their coding skills. So, even in today's ever-evolving software landscape, these books are worth their weight in gold.

I highly recommend two books: "Clean Code" and "Clean Architecture," both authored by Robert Martin. These books have been recommended countless times, and for good reason. They encapsulate tried and tested software engineering best practices that every software engineer should be aware of.

While not every principle in these books may directly apply to modern engineering with distributed architectures, they remain invaluable when it comes to writing solid and maintainable code. These books provide numerous examples of good and bad code, as well as good and bad design, making it immensely helpful for anyone looking to improve their coding skills. So, even in today's ever-evolving software landscape, these books are worth their weight in gold.

Learning about distributed systems can be quite daunting due to its vastness, and this book stands out for its elegant approach to covering a wide range of topics without overwhelming beginners.

What makes this book special is its ability to cater to both newcomers and intermediate-level readers. It starts from the absolute basics, assuming no prior knowledge, and gradually progresses to more complex concepts. Even if you already have some experience in distributed systems, you can still gain valuable insights from this book. It condenses a wealth of information into a compact volume, making it an excellent resource for anyone looking to understand distributed systems effectively.

"Designing Data-Intensive Applications" by Martin Kleppmann is often regarded as the Holy Grail of distributed systems books. It's notably more in-depth compared to the first book I recommended. If you've already read the first book or find it too basic for your level of understanding, this is an excellent next step in your journey to mastering distributed architectures.

While the first book provides a high-level overview and a basic understanding of distributed systems, "Designing Data-Intensive Applications" delves deeper into the concepts and mechanics of how distributed systems operate. It explores the intricate trade-offs you encounter when working with distributed systems, making it an indispensable resource for those seeking a deeper understanding of this complex field.

"Software Architecture: The Hard Parts" is a fantastic book to consider, especially if you're looking for real-world examples and anecdotes that explain why distributed architectures are challenging. This book is a valuable resource as it offers insights that come directly from experience.

However, it's worth noting that this book is not suitable for beginners. You should have a solid understanding of the basics of distributed systems, preferably having read the previous two books I recommended, or have a few years of experience working with distributed architectures. This book is tailored for those who are already familiar with the fundamentals and are looking to deepen their knowledge in this complex field.

If you're looking to enhance your knowledge in the field of DevOps, I recommend "Lean DevOps" by Robert Benefit. This book offers a straightforward and concise approach to covering all the essential areas without overwhelming you with unnecessary information. It's an easy and simple read, making it a valuable resource for anyone seeking to improve their understanding of DevOps.

This book is an excellent introduction to the world of machine learning. It provides a solid foundation by covering the basics of common machine learning concepts like neural networks and deep learning, which are the basis for models like ChatGPT-3. However, it's important to note that this book is not for those seeking in-depth or academic-level information.

The 100 Page Machine Learning Book is perfect for beginners who want to grasp the breadth of machine learning concepts and is an excellent starting point for anyone looking to embark on their machine learning journey in 2023.