Familiarize yourself with advanced deep learning architectures
Explore newer topics, such as handling hidden bias in data and algorithm explainability
Get to grips with different programming algorithms and choose the right data structures for their optimal implementation

Description

The ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book 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. 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. You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT. 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.

Who is this book for?

This computer science book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code. Whether you are a beginner looking to learn the most used algorithms concisely or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful. Python programming experience is a must, knowledge of data science will be helpful but not necessary.

What you will learn

Design algorithms for solving complex problems
Become familiar with neural networks and deep learning techniques
Explore existing data structures and algorithms found in Python libraries
Implement graph algorithms for fraud detection using network analysis
Delve into state-of-the-art algorithms for proficient Natural Language Processing illustrated with real-world examples
Create a recommendation engine that suggests relevant movies to subscribers
Grasp the concepts of sequential machine learning models and their foundational role in the development of cutting-edge LLMs

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Sandra Patricia Bermudez Kasperczak Feb 22, 2024

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Kam F Siu Jan 30, 2024

N/A Feb 19, 2024

Kevin Killion Feb 15, 2024

The TITLE of this item is very misleading. It SHOULD be titled, ""50 Algorithms Every PYTHON Programmer Should Know". Plus, the files in the sample code are unreadable. Here is what I wrote to you previously: It's only ten bucks, but this is a big disappointment so far. I've been programming since about 1971,and have built and sold many projects. But I saw a few topics in the ebook "50 Algorithms Every Programmer Should Know" that I wanted to know more about, so I purchased it just now. 1) NOWHERE in the promo email or web page was there a warning that the sample code in this was in Python. That alone would have killed my interest in buying it. 2) I eventually figured out how to download the sample code as a single ZIP. However, none of my tools are coping with whatever this code uses for line endings. BBEdit can usually deal with anything but all I get is a single line, even after switching line ending settings. SKEdit, TextEdit and even Word fail as well. Is it some kind of mystical Python format????? It's only ten bucks, but still what a waste. Kevin Killion

N/A Feb 21, 2024

50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography , Second Edition

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