Advanced Machine Learning : Fundamentals and algorithms
Our book explains learning algorithms related to real-world problems, with implementations in languages like R, Python, etc. Key Features: Basic understanding of machine learning algorithms via MATLAB, R, and Python ; Inclusion of examples related to real-world problems, case studies, and questions...
Uloženo v:
| Hlavní autoři: | , , |
|---|---|
| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
New Delhi :
BPB Publications
2024.
Paris : Cyberlibris |
| On-line přístup: | Accès Université d'Orléans et IFPM |
| Poznámka: |
Couverture. https://static2.cyberlibris.com/books_upload/136pix/9789355516343.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Advanced Machine Learning, Fundamentals and algorithms, Dr. Amit Kumar Tyagi, Dr. Khushboo Tripathi, Dr. Avinash Kumar Sharma, New Delhi, BPB Publications, 2024, 1 vol. (634 p.), 978-93-5551-634-3 |
Obsah:
- 1. Introduction to Machine Learning
- 2. Statistical Analysis
- 3. Linear Regression
- 4. Logistic Regression
- 5. Decision Trees
- 6. Random Forest
- 7. Rule-Based Classifiers
- 8. Naïve Bayesian Classifier
- 9. K-Nearest Neighbors Classifiers
- 10. Support Vector Machine
- 11. K-Means Clustering
- 12. Dimensionality Reduction
- 13. Association Rules Mining and FP Growth
- 14. Reinforcement Learning
- 15. Applications of ML Algorithms
- 16. Applications of Deep Learning
- 17. Advance Topics and Future Directions