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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

The Evolution of ANNs

In the preceding section, we looked into a simple neural network without any layers called a perceptron. The perceptron was found to have serious limitations, and in 1969, Marvin Minsky and Seymour Papert worked on research that led to the conclusion that a perceptron is incapable of learning any complex logic.

In fact, they showed that it would be a struggle to learn even logical functions as simple as XOR. That led to a decrease in interest in machine learning in general, and neural networks in particular, and started an era that is now known as the AI winter. Researchers around the world would not take AI seriously, thinking that it was incapable of solving any complex problems.

One of the primary reasons for the so-called AI winter was the limitation of the hardware capabilities available at that time. Either the necessary computing...

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