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PyTorch for Deep Learning with Python Bootcamp

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Learn how to create state of the art neural networks for deep learning with Facebook's PyTorch Deep Learning library!


1 - Course Overview Installs and Setup
  • 1 - COURSE OVERVIEW LECTURE PLEASE DO NOT SKIP
  • 1 - PYTORCH-NOTEBOOKS.zip
  • 2 - Installation and Environment Setup
  • 2 - Link for yml environment file.txt
  • 2 - PYTORCH-NOTEBOOKS.zip

  • 2 - COURSE OVERVIEW CONFIRMATION CHECK
  • 1 - DID YOU WATCH THE COURSE OVERVIEW LECTURE.html

  • 3 - Crash Course NumPy
  • 3 - Introduction to NumPy
  • 4 - NumPy Arrays
  • 5 - NumPy Arrays Part Two
  • 6 - Numpy Index Selection
  • 7 - NumPy Operations
  • 8 - Numpy Exercises
  • 9 - Numpy Exercises Solutions

  • 4 - Crash Course Pandas
  • 10 - Pandas Overview
  • 11 - Pandas Series
  • 12 - Pandas DataFrames Part One
  • 13 - Pandas DataFrames Part Two
  • 14 - GroupBy Operations
  • 15 - Pandas Operations
  • 16 - Data Input and Output
  • 17 - Pandas Exercises
  • 18 - Pandas Exercises Solutions

  • 5 - PyTorch Basics
  • 19 - PyTorch Basics Introduction
  • 20 - Tensor Basics
  • 21 - Tensor Basics Part Two
  • 22 - Tensor Operations
  • 23 - Tensor Operations Part Two
  • 24 - PyTorch Basics Exercise
  • 25 - PyTorch Basics Exercise Solutions

  • 6 - Machine Learning Concepts Overview
  • 26 - What is Machine Learning
  • 27 - Supervised Learning
  • 28 - Overfitting
  • 29 - Evaluating Performance Classification Error Metrics
  • 30 - Evaluating Performance Regression Error Metrics
  • 31 - Unsupervised Learning

  • 7 - ANN Artificial Neural Networks
  • 32 - Introduction to ANN Section
  • 33 - Theory Perceptron Model
  • 34 - Theory Neural Network
  • 35 - Theory Activation Functions
  • 36 - MultiClass Classification
  • 37 - Theory Cost Functions and Gradient Descent
  • 38 - BackPropagation Explained 1.txt
  • 38 - Backpropagation Great Theory Book.txt
  • 38 - Theory BackPropagation
  • 39 - PyTorch Gradients
  • 40 - Linear Regression with PyTorch
  • 41 - Linear Regression with PyTorch Part Two
  • 42 - DataSets with PyTorch
  • 43 - Basic Pytorch ANN Part One
  • 44 - Basic PyTorch ANN Part Two
  • 45 - Basic PyTorch ANN Part Three
  • 46 - Introduction to Full ANN with PyTorch
  • 47 - Full ANN Code Along Regression Part One Feature Engineering
  • 48 - Full ANN Code Along Regression Part 2 Categorical and Continuous Features
  • 49 - Full ANN Code Along Regression Part Three Tabular Model
  • 50 - Full ANN Code Along Regression Part Four Training and Evaluation
  • 51 - Full ANN Code Along Classification Example
  • 52 - ANN Exercise Overview
  • 53 - ANN Exercise Solutions

  • 8 - CNN Convolutional Neural Networks
  • 54 - Introduction to CNNs
  • 55 - Understanding the MNIST data set
  • 56 - ANN with MNIST Part One Data
  • 57 - ANN with MNIST Part Two Creating the Network
  • 58 - ANN with MNIST Part Three Training
  • 59 - ANN with MNIST Part Four Evaluation
  • 60 - Image Filters and Kernels
  • 61 - Convolutional Layers
  • 62 - Pooling Layers
  • 63 - MNIST Data Revisited
  • 64 - MNIST with CNN Code Along Part One
  • 65 - MNIST with CNN Code Along Part Two
  • 66 - MNIST with CNN Code Along Part Three
  • 67 - CIFAR10 DataSet with CNN Code Along Part One
  • 68 - CIFAR10 DataSet with CNN Code Along Part Two
  • 69 - Google Drive Download Link for CATSDOGS zip file.txt
  • 69 - Loading Real Image Data Part One
  • 70 - Loading Real Image Data Part Two
  • 71 - CNN on Custom Images Part One Loading Data
  • 72 - CNN on Custom Images Part Two Training and Evaluating Model
  • 73 - CNN on Custom Images Part Three PreTrained Networks
  • 74 - CNN Exercise
  • 75 - CNN Exercise Solutions

  • 9 - Recurrent Neural Networks
  • 76 - Introduction to Recurrent Neural Networks
  • 77 - RNN Basic Theory
  • 78 - Vanishing Gradients
  • 79 - LSTMS and GRU
  • 80 - RNN Batches Theory
  • 81 - RNN Creating Batches with Data
  • 82 - Basic RNN Creating the LSTM Model
  • 83 - Basic RNN Training and Forecasting
  • 84 - RNN on a Time Series Part One
  • 85 - RNN on a Time Series Part Two
  • 86 - RNN Exercise
  • 87 - RNN Exercise Solutions

  • 10 - Using a GPU with PyTorch and CUDA
  • 88 - CUDA with PyTorch.txt
  • 88 - NVIDIA CUDA Installation Page.txt
  • 88 - Official Docs on Pytorch on Google Colab.txt
  • 88 - PyTorch Official Install Page.txt
  • 88 - PyTorch on AWS.txt
  • 88 - PyTorch on Google Cloud Platform.txt
  • 88 - PyTorch on Microsoft Azure.txt
  • 88 - Why do we need GPUs
  • 89 - Using GPU for PyTorch

  • 11 - NLP with PyTorch
  • 90 - Introduction to NLP with PyTorch
  • 91 - Encoding Text Data
  • 92 - Generating Training Batches
  • 93 - Creating the LSTM Model
  • 94 - Training the LSTM Model
  • 95 - Google Drive Link for another Model.txt
  • 95 - OUR MODEL FOR DOWNLOAD.html
  • 96 - Generating Predictions

  • 12 - BONUS SECTION THANK YOU
  • 97 - BONUS LECTURE.html
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    تاریخ انتشار: ۶ فروردین ۱۴۰۳
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