Dive into Deep Learning

Table Of Contents

2. Crashcourse in the Preliminaries

If you are in a hurry, this chapter has all the details you need to get a taste of deep learning. If you like to take the scenic route, we still recommend that you read it, since it will explain how to set up Apache MXNet, how to use automatic differentiation and how to manipulate data and memory. We also provide quick primers on linear algebra and statistics, designed to help readers to get up to speed on the basics.

• 2.1. Data Manipulation
  • 2.1.1. Getting Started
  • 2.1.2. Operations
  • 2.1.3. Broadcast Mechanism
  • 2.1.4. Indexing and Slicing
  • 2.1.5. Saving Memory
  • 2.1.6. Mutual Transformation of NDArray and NumPy
  • 2.1.7. Exercises
  • 2.1.8. Scan the QR Code to Discuss
• 2.2. Linear Algebra
  • 2.2.1. Scalars
  • 2.2.2. Vectors
  • 2.2.3. Length, dimensionality and shape
  • 2.2.4. Matrices
  • 2.2.5. Tensors
  • 2.2.6. Basic properties of tensor arithmetic
  • 2.2.7. Sums and means
  • 2.2.8. Dot products
  • 2.2.9. Matrix-vector products
  • 2.2.10. Matrix-matrix multiplication
  • 2.2.11. Norms
  • 2.2.12. Norms and objectives
  • 2.2.13. Intermediate linear algebra
  • 2.2.14. Summary
  • 2.2.15. Scan the QR Code to Discuss
• 2.3. Automatic Differentiation
  • 2.3.1. A Simple Example
  • 2.3.2. Training Mode and Prediction Mode
  • 2.3.3. Computing the Gradient of Python Control Flow
  • 2.3.4. Head gradients and the chain rule
  • 2.3.5. Summary
  • 2.3.6. Exercises
  • 2.3.7. Scan the QR Code to Discuss
• 2.4. Probability and Statistics
  • 2.4.1. Basic probability theory
  • 2.4.2. Dealing with multiple random variables
  • 2.4.3. Conditional independence
  • 2.4.4. Summary
  • 2.4.5. Exercises
  • 2.4.6. Scan the QR Code to Discuss
• 2.5. Naive Bayes Classification
  • 2.5.1. Optical Character Recognition
  • 2.5.2. Summary
  • 2.5.3. Exercises
  • 2.5.4. Scan the QR Code to Discuss
• 2.6. Sampling
  • 2.6.1. Uniform Distribution
  • 2.6.2. The categorical distribution
  • 2.6.3. The Normal distribution
  • 2.6.4. More distributions
  • 2.6.5. Scan the QR Code to Discuss
• 2.7. Documentation
  • 2.7.1. Finding all the functions and classes in the module
  • 2.7.2. Finding the usage of specific functions and classes
  • 2.7.3. API Documentation
  • 2.7.4. Exercise
  • 2.7.5. Scan the QR Code to Discuss

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1. Introduction

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2.1. Data Manipulation