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40 Algorithms Every Programmer Should Know

You're reading from   40 Algorithms Every Programmer Should Know Hone your problem-solving skills by learning different algorithms and their implementation in Python

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781789801217
Length 382 pages
Edition 1st Edition
Languages
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Author (1):
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Imran Ahmad Imran Ahmad
Author Profile Icon Imran Ahmad
Imran Ahmad
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Toc

Table of Contents (19) Chapters Close

Preface 1. Section 1: Fundamentals and Core Algorithms
2. Overview of Algorithms FREE CHAPTER 3. Data Structures Used in Algorithms 4. Sorting and Searching Algorithms 5. Designing Algorithms 6. Graph Algorithms 7. Section 2: Machine Learning Algorithms
8. Unsupervised Machine Learning Algorithms 9. Traditional Supervised Learning Algorithms 10. Neural Network Algorithms 11. Algorithms for Natural Language Processing 12. Recommendation Engines 13. Section 3: Advanced Topics
14. Data Algorithms 15. Cryptography 16. Large-Scale Algorithms 17. Practical Considerations 18. Other Books You May Enjoy

Understanding supervised machine learning

Machine learning focuses on using data-driven approaches to create autonomous systems that can help us to make decisions with or without human supervision. In order to create these autonomous systems, machine learning uses a group of algorithms and methodologies to discover and formulate repeatable patterns in data. One of the most popular and powerful methodologies used in machine learning is the supervised machine learning approach. In supervised machine learning, an algorithm is given a set of inputs, called features, and their corresponding outputs, called target variables. Using a given dataset, a supervised machine learning algorithm is used to train a model that captures the complex relationship between the features and target variables represented by a mathematical formula. This trained model is the basic vehicle that...

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