Deep Neural Networks with PyTorch

Week2. Linear Regression with PyTorch

Linear Regression

  • Linear Regression Prediction

  • Linear Regression Training

  • Loss

  • Gradient Descent

  • Cost

  • Linear Regression PyTorch

  • PyTorch Linear Regression Training Slope and Bias

Linear Regression PyTorch Way

  • Stochastic Gradient Descent

  • Mini-Batch Gradient Descent

  • Optimization in PyTorch

  • Training, Validation and Test Split

Week3. Multiple Linear Regression and Logistic Regression

Multiple Input Output Linear Regression

  • Multiple Linear Regression Prediction

  • Multiple Linear Regression Training

  • Linear Regression Multiple Outputs

  • Multiple Output Linear Regression Training

Logistic Regression for Classification

  • Linear Classifier

  • Logistic Regression: Prediction

  • Bernoulli Distribution and Maximum Likelihood Estimation

  • Logistic Regression Cross Entropy Loss

Week4. Softmax Regression and Shallow Neural Networks

Softmax Regression

  • Softmax

  • Softmax Function: Using Lines to Classify Data

  • Softmax PyTorch

Shallow Neural Networks

  • What’s Neural Network

  • More Hidden Neurons

  • Neural Networks with Multiple Dimensional Input

  • Multi-Class Neural Networks

  • Backpropagation

  • Activation Functions

Week5. Deep Networks

  • Deep Neural Networks

  • Deeper Neural Networks: nn.ModuleList()

  • Dropout

  • Neural Network Initialization Weights

  • Gradient Descent with Momentum

  • Batch Normalization

Week6. Convolutional Neural Network

  • Convolution

  • Activation Functions and Max Polling

  • Multiple Input and Output Channel

  • Convolutional Neural Network

  • TORCH-VISION-MODELS

Reference