Seven Metaheuristics to Learn for your Next Data Science Project

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Seven Metaheuristics to Learn for your Next Data Science Project

Seven Metaheuristics to Learn for your Next Data Science ProjectA Video Book on Metaheuristic Algorithms

Author Name: Mrinmoy Majumder | Format: Paperback | Genre : Educational & Professional | Other Details

The video book Seven Metaheuristics to Learn for your Next Data Science Project will assist you in easily and clearly understanding the seven most popular nature-based or metaheuristic algorithms. Additionally, 50 project ideas and 50 practice numbers are included. The Content of the book is as follows :

1. INTRODUCTION

1.1. Types of Metaheuristics

1.2. Applications in Data Science 

1.3. Advantages and Limitations 

1.4. Comparison with other optimization techniques

2. OVERVIEW OF METAHEURISTICS

2.1. Application of Metaheuristics 

2.2. Application of Metaheuristics in Applied Fields

2.3. Classification of Metaheuristic Algorithms

2.4. Working Principle

2,5. Limitations of Metaheuristic Algorithms

2.5. Future Scopes of Metaheuristics

3. METHOD I: ARTIFICIAL NEURAL NETWORK OR ANN

4. METHOD II: POLYNOMIAL NEURAL NETWORK OR PNN

5. METHOD III: GLOW WORM ALGORITHM OR GWA

6. METHOD IV: MINE BLAST ALGORITHM OR MBA

7. METHOD V: WATER CYCLE ALGORITHM OR WCA

8. METHOD VI: DOLPHIN ECHOLOCATION ALGORITHM OR DEA

9. METHOD VII : GENETIC ALGORITHM OR GA

10. CONCLUSION 

10.1. Project Ideas

10.2. Numerical Problems

The Project ideas and numerical problems are often updated.

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