Machine Learning with Python Theory and Implementation /
This book is meant as a textbook for undergraduate and graduate students who are willing to understand essential elements of machine learning from both a theoretical and a practical perspective. The choice of the topics in the book is made based on one criterion: whether the practical utility of a c...
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| Natura: | Elettronico eBook |
| Lingua: | inglese |
| Pubblicazione: |
Cham :
Springer International Publishing : Imprint: Springer,
2023.
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| Edizione: | 1st ed. 2023. |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1007/978-3-031-33342-2 |
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Sommario:
- Preface
- About This Book
- 1. Introduction
- 2. Getting Started with Python
- 3. Three Fundamental Python Packages
- 4. Supervised Learning in Practice: The First Application Using Scikit-Learn. - 5. K-Nearest Neighbors
- 6. Linear Models
- 7. Decision Trees
- 8. Ensemble Learning
- 9. Model Evaluation and Selection
- 10. Feature Selection
- 11. Assembling Various Learning Stages
- 12. Clustering
- 13. Deep Learning with Keras-TensorFlow. - 14. Convolutional Neural Networks
- 15. Recurrent Neural Networks
- References.