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PyTorch Tutorial 06 Training Pipeline Model Loss and Optimizer

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Lessons List | 22 Lesson

PyTorch Tutorial 01 Installation

PyTorch Tutorial 01 Installation

PyTorch Tutorial 02 Tensor Basics

PyTorch Tutorial 02 Tensor Basics

PyTorch Tutorial 03 Gradient Calculation With Autograd

PyTorch Tutorial 03 Gradient Calculation With Autograd

PyTorch Tutorial 04 Backpropagation Theory With Example

PyTorch Tutorial 04 Backpropagation Theory With Example

PyTorch Tutorial 05 Gradient Descent with Autograd and Backpropagation

PyTorch Tutorial 05 Gradient Descent with Autograd and Backpropagation

PyTorch Tutorial 06 Training Pipeline Model Loss and Optimizer

PyTorch Tutorial 06 Training Pipeline Model Loss and Optimizer

PyTorch Tutorial 07 Linear Regression

PyTorch Tutorial 07 Linear Regression

PyTorch Tutorial 08 Logistic Regression

PyTorch Tutorial 08 Logistic Regression

PyTorch Tutorial 09 Dataset and DataLoader Batch Training

PyTorch Tutorial 09 Dataset and DataLoader Batch Training

PyTorch Tutorial 10 Dataset Transforms

PyTorch Tutorial 10 Dataset Transforms

PyTorch Tutorial 11 Softmax and Cross Entropy

PyTorch Tutorial 11 Softmax and Cross Entropy

PyTorch Tutorial 12 Activation Functions

PyTorch Tutorial 12 Activation Functions

PyTorch Tutorial 13 Feed Forward Neural Network

PyTorch Tutorial 13 Feed Forward Neural Network

PyTorch Tutorial 14 Convolutional Neural Network CNN

PyTorch Tutorial 14 Convolutional Neural Network CNN

PyTorch Tutorial 15 Transfer Learning

PyTorch Tutorial 15 Transfer Learning

PyTorch Tutorial 16 How To Use The TensorBoard

PyTorch Tutorial 16 How To Use The TensorBoard

PyTorch Tutorial 17 Saving and Loading Models

PyTorch Tutorial 17 Saving and Loading Models

Create Deploy A Deep Learning App PyTorch Model Deployment With Flask Heroku

Create Deploy A Deep Learning App PyTorch Model Deployment With Flask Heroku

PyTorch RNN Tutorial Name Classification Using A Recurrent Neural Net

PyTorch RNN Tutorial Name Classification Using A Recurrent Neural Net

PyTorch Tutorial RNN LSTM GRU Recurrent Neural Nets

PyTorch Tutorial RNN LSTM GRU Recurrent Neural Nets

PyTorch Lightning Tutorial Lightweight PyTorch Wrapper For ML Researchers

PyTorch Lightning Tutorial Lightweight PyTorch Wrapper For ML Researchers

PyTorch LR Scheduler Adjust The Learning Rate For Better Results

PyTorch LR Scheduler Adjust The Learning Rate For Better Results

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Installation instructions were dated. Easier to follow examples would be better 2025-04-30

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Course Description

A good use case of Numpy is quick experimentation and small projects because Numpy is a light weight framework compared to PyTorch. Moreover, PyTorch lacks a few advanced features as you'll read below so it's strongly recommended to use numpy in those cases .

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