Tackle computer science problems using both fundamental and modern algorithms in machine learning

The ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. But a major issue for them is to dive into a big pool of algorithms and find the most relevant ones. 

This book (50 Algorithms Every Programmer Should Know) will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works. 

You'll start with an introduction to algorithms and discover various algorithm design techniques before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them. Additionally, the book will delve into modern deep learning techniques, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Recurrent Neural Networks (RNNs), providing insights into their applications. The expansive realm of Generative AI and Large Language Models (LLMs) such as ChatGPT will also be explored, unraveling the algorithms, methodologies, and architectures that drive their implementation. 

Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use. Finally, you'll become well-versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks. 

By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms, including modern deep learning techniques. 

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