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50 Algorithms Every Programmer Should Know - Second Edition

You're reading from  50 Algorithms Every Programmer Should Know - Second Edition

Product type Book
Published in Sep 2023
Publisher Packt
ISBN-13 9781803247762
Pages 538 pages
Edition 2nd Edition
Languages
Author (1):
Imran Ahmad Imran Ahmad
Profile icon Imran Ahmad

Table of Contents (22) Chapters

Preface 1. Section 1: Fundamentals and Core Algorithms
2. Overview of Algorithms 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. Understanding Sequential Models 13. Advanced Sequential Modeling Algorithms 14. Section 3: Advanced Topics
15. Recommendation Engines 16. Algorithmic Strategies for Data Handling 17. Cryptography 18. Large-Scale Algorithms 19. Practical Considerations 20. Other Books You May Enjoy
21. Index

Activation Functions

An activation function formulates how the inputs to a particular neuron will be processed to generate an output.As shown in the following diagram, each of the neurons in a neural networkneural network has an activation function that determines how inputs will be processed:

Figure 8.9: Activation Function

In the preceding diagram, we can see that the results generated by an activation function are passed on to the output. The activation function sets the criteria that how the values of the inputs are supposed to be interpreted to generate an output.For exactly the same input values, different activation functions will produce different outputs. Understanding how to select the right activation function is important when using neural neural networks to solve problems.Let's now look into these activation functions one by one.

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