2.1. Data manipulation
2.1.1. To work
2.1.2. Activities
2.1.3. Broadcasting mechanism
2.1.4. Indexing and segmenting
2.1.5. Save memory
2.1.6. Conversion to other Python objects
2.1.7. Resume
2.1.8. Assignments
2.2. Data preprocessing
2.2.1. Read the dataset
2.2.2. Dealing with missing data
2.2.3. Conversion to the tensor format
2.2.4. Resume
2.2.5. Assignments
2.3. Linear algebra
2.3.1. Scalars
2.3.2. Vectors
2.3.3. Matrices
2.3.4. Tensors
2.3.5. Basic properties of tensor calculations
2.3.6. Decrease
2.3.7. Dot products
2.3.8. Matrix-Vector Products
2.3.9. Matrix-matrix multiplication
2.3.10. Standards
2.3.11. More about linear algebra
2.3.12. Resume
2.3.13. Assignments
2.4. Calculation
2.4.1. Derivatives and differentiation
2.4.2. Partial derivatives
2.4.3. Expired
2.4.4. Chain rule
2.4.5. Resume
2.4.6. Assignments
2.5. Automatic differentiation
2.5.1. A simple example
2.5.2. Backwards for non-scalar variables
2.5.3. Disconnect calculation
2.5.4. Calculating the gradient of the Python control flow
2.5.5. Resume
2.5.6. Assignments
2.6. Probability
2.6.1. Basic probability theory
2.6.2. Dealing with multiple random variables
2.6.3. Expectation and variance
2.6.4. Resume
2.6.5. Assignments
2.7. Documentation
2.7.1. Find all functions and classes in a module
2.7.2. Find the use of specific functions and classes
2.7.3. Resume
2.7.4. Assignments

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