This section introduces us to the core aspects of algorithms. We will explore what an algorithm is and how to design it, and also learn about the data structures used in algorithms. This section also gives a deep idea on sorting and searching algorithms along with the algorithms to solve graphical problems. The chapters included in this section are:
-
Book Overview & Buying
-
Table Of Contents
-
Feedback & Rating
40 Algorithms Every Programmer Should Know
By :
40 Algorithms Every Programmer Should Know
By:
Overview of this book
Algorithms have always played an important role in both the science and practice of computing. Beyond traditional computing, the ability to use algorithms to solve real-world problems is an important skill that any developer or programmer must have. This book will help you not only to develop the skills to select and use an algorithm to solve real-world problems 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, such as searching and sorting, with the help of practical examples. As you advance to a more complex set of algorithms, you'll learn about linear programming, page ranking, and graphs, and even work with machine learning algorithms, understanding the math and logic behind them. Further on, case studies such as weather prediction, tweet clustering, and movie recommendation engines will show you how to apply these algorithms optimally. 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 book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.
Table of Contents (19 chapters)
Preface
Section 1: Fundamentals and Core Algorithms
Free Chapter
Overview of Algorithms
Data Structures Used in Algorithms
Sorting and Searching Algorithms
Designing Algorithms
Graph Algorithms
Section 2: Machine Learning Algorithms
Unsupervised Machine Learning Algorithms
Traditional Supervised Learning Algorithms
Neural Network Algorithms
Algorithms for Natural Language Processing
Recommendation Engines
Section 3: Advanced Topics
Data Algorithms
Cryptography
Large-Scale Algorithms
Practical Considerations
Other Books You May Enjoy
Customer Reviews
