40 Algorithms Every Programmer Should Know: Python algorithms to live by to enhance your problem-solving skills, 2nd Edition
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Packt Publishing - ebooks Account
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 tackle problems in the real world by understanding 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.
Case studies on weather prediction, tweet clustering, and movie recommendation engines will show you how to apply these algorithms optimally. Then you will focus on deep learning algorithms and will 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.
About the Author
- 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
- Work with machine learning algorithms to cluster similar tweets and process Twitter data in real time
- Create a recommendation engine that suggests relevant movies to subscribers
- Implement foolproof security using symmetric and asymmetric encryption on Google Cloud Platform
- Overview of Algorithms
- Data Structures Used in Algorithms
- Sorting and Searching Algorithms
- Designing Algorithms
- Graph Algorithms
- Unsupervised Machine Learning Algorithms
- Traditional Supervised Learning Algorithms
- Neural Network Algorithms
- Advanced Deep Learning Algorithms
- Algorithms for Natural Language Processing
- Recommendation Engines
- Data Algorithms
- Cryptography
- Large-Scale Algorithms
- Practical Considerations
