Book description
- Review machine learning fundamentals such as overfitting, underfitting, and regularization.
- Understand deep learning fundamentals such as feed-forward networks, convolution neural networks, recurrent neural networks, automatic differentiation, and stochastic gradient descent.
- Apply in-depth linear algebra with PyTorch
- Explore PyTorch fundamentals andits building blocks
- Work with tuning and optimizing models
Table of contents
- Cover
- Front Matter
- 1. Introduction to Machine Learning and Deep Learning
- 2. Introduction to PyTorch
- 3. Feed-Forward Neural Networks
- 4. Automatic Differentiation in Deep Learning
- 5. Training Deep Leaning Models
- 6. Convolutional Neural Networks
- 7. Recurrent Neural Networks
- 8. Recent Advances in Deep Learning
- Back Matter
Product information
- Title: Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch
- Author(s):
- Release date: April 2021
- Publisher(s): Apress
- ISBN: 9781484253649
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