Exercises' solutions of the book Dive Into Deep Learning (MXNet version)
- 2: Preliminaries
- 2.1: Data Manipulation
- 2.2: Data Preprocessing
- 2.3: Linear Algebra
- 2.4: Calculus
- 2.5: Automatic Differentiation
- 2.6: Probability and Statistics
- 3: Linear Neural Networks
- 4: Multilayer Perceptrons
- 5: Deep Learning Computation
- 6: Convolutional Neural Networks
- 7: Modern Convolutional Neural Networks
- 8: Recurrent Neural Networks
- 9: Modern Recurrent Neural Networks
- 10: Attention Mechanisms
- 11: Optimization Algorithms
- 12: Computational Performance
- 13: Computer Vision
- 14: Natural Language Processing: Pretraining
- 15: Natural Language Processing: Applications
- 16: Recommender Systems
- 17: Generative Adversarial Networks