Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2
Себастьян Рашка, Вахид Мирджалили
| Издательство: | PACKT Publishing |
Лучшая подборка с книгой
1. Giving Computers the Ability to Learn from Data
2. Training Simple ML Algorithms for Classification
3. ML Classifiers Using scikit-learn
4. Building Good Training Datasets - Data Preprocessing
5. Compressing Data via Dimensionality Reduction
6. Best Practices for Model Evaluation and Hyperparameter Tuning
7. Combining Different Models for Ensemble Learning
8. Applying ML to Sentiment Analysis
9. Embedding a ML Model into a Web Application
10. Predicting Continuous Target Variables with Regression Analysis
11. Working with Unlabeled Data - Clustering Analysis
12. Implementing Multilayer Artificial Neural Networks
13. Parallelizing Neural Network Training with TensorFlow
14. TensorFlow Mechanics
15. Classifying Images with Deep Convolutional Neural Networks
16. Modeling Sequential Data Using Recurrent Neural Networks
17. GANs for Synthesizing New Data
18. RL for Decision Making in Complex Environments
ISBN: 978-1789955750
Год издания: 2019
Dimensions: 7.5 x 1.74 x 9.25 inches.
Paperback: 770 pages.
Кураторы
knwnw
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