Dive-into-deep-learning

Linear Neural Networks-The basics of deep neural networks

1. Linear Regression model
2. Basic Elements of Linear Regression
3. Generating the Dataset from normal distribution
4. Visualize the features and labels variable
5. Reading the Dataset as small batches
6. Initializing Model Parameters
7. Defining the Model
8. Defining the Loss Function
9. Defining the Optimization Algorithm
10. Training