Seven Metaheuristics to Learn for your Next Data Science Project is a video book that will help you learn the seven most contemporary nature-based or metaheuristic algorithms simply and lucidly. It also includes 50 project ideas and 50 numericals for your practice.

The content of the book is as follows :1. INTRODUCTION1.

1. Types of Metaheuristics1.

2. Applications in Data Science1.

3. Advantages and Limitations1.

4. Comparison with other optimization techniques2.

OVERVIEW OF METAHEURISTICS2. 1.

Application of Metaheuristics2. 2.

Application of Metaheuristics in Applied Fields2. 3.

Classification of Metaheuristic Algorithms2. 4.

Working Principle2,5. Limitations of Metaheuristic Algorithms2.

5. Future Scopes of Metaheuristics3.

METHOD I: ARTIFICIAL NEURAL NETWORK OR ANN4. METHOD II: POLYNOMIAL NEURAL NETWORK OR PNN5.

METHOD III: GLOW WORM ALGORITHM OR GWA6. METHOD IV: MINE BLAST ALGORITHM OR MBA7.

METHOD V: WATER CYCLE ALGORITHM OR WCA8. METHOD VI: DOLPHIN ECHOLOCATION ALGORITHM OR DEA9.

METHOD VII : GENETIC ALGORITHM OR GA10. CONCLUSION10.

1. Project Ideas10.

2. Numerical ProblemsThe Project ideas and numerical problems are often updated.

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