Book Image

50 Algorithms Every Programmer Should Know - Second Edition

By : Imran Ahmad
4 (5)
Book Image

50 Algorithms Every Programmer Should Know - Second Edition

4 (5)
By: Imran Ahmad

Overview of this book

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.
Table of Contents (22 chapters)
Free Chapter
1
Section 1: Fundamentals and Core Algorithms
7
Section 2: Machine Learning Algorithms
14
Section 3: Advanced Topics
20
Other Books You May Enjoy
21
Index

Areas of practical applications

Recommendation systems play a pivotal role in our daily digital interactions. To truly understand their significance, let’s delve into their applications across various industries.

Based on the comprehensive details provided about Netflix’s use of data science and its recommendation system, let’s look at the restructured statement addressing the points mentioned.

Netflix’s mastery of data-driven recommendations

Netflix, a leader in streaming, has harnessed data analytics to fine-tune content recommendations, with 800 engineers in Silicon Valley advancing this effort. Their emphasis on data-driven strategies is evident in the Netflix Prize challenge. The winning team, BellKor’s Pragmatic Chaos, used 107 diverse algorithms, from matrix factorization to restricted Boltzman machines, investing 2,000 hours in its development.

The results were a significant 10.06% improvement in their “Cinematch”...