├── Images └── Screenshot (74).png └── Readme.md /Images/Screenshot (74).png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/param087/Pytorch-tutorial-on-Google-colab/HEAD/Images/Screenshot (74).png -------------------------------------------------------------------------------- /Readme.md: -------------------------------------------------------------------------------- 1 | # PyTorch tutorial on google colab notebook 2 | Some notebook contains the installation command for PyTorch but now google colab have pytorch pre-install. 3 | ### [reference - https://pytorch.org/tutorials/](https://pytorch.org/tutorials/) 4 | 5 | *** 6 | ## Requirements - Chrome Browser and Google drive login 7 | 8 | 9 | *** 10 | # Getting Started 11 | * Deep Learning with PyTorch: A 60 Minute Blitz 12 | * [What is PyTorch?](https://colab.research.google.com/drive/1SCW0WNW4716jV803YJiRvsvcQezR0Tzx) 13 | * [Autograd: Automatic Differentiation](https://colab.research.google.com/drive/1XW3phQbownypM9xyG0_05hzxVe5lc1Yr) 14 | * [Neural Networks](https://colab.research.google.com/drive/1kYBwZfxC-L7dvj51NcNdS1VSQPT0IjqG) 15 | * [Training a Classifier](https://colab.research.google.com/drive/1v-rWBOFdqfBRaNcx27uC9q82K9XrXjHx) 16 | * [Optional: Data Parallelism](https://colab.research.google.com/drive/1e6FRN2YKSJlefWrZKPp4Hy-n5l9ckhC-) 17 | * [Data Loading and Processing Tutorial](https://colab.research.google.com/drive/13BxH3nkqwlU_ZCplU2Czn8cgP7nnR0xR) 18 | * Learning PyTorch with Examples 19 | * Tensors 20 | * [Warm-up: numpy](https://colab.research.google.com/drive/1uT6cq0JQZBhw4M0EJZUoikekES2ltNGw) 21 | * [PyTorch: Tensors](https://colab.research.google.com/drive/16GkGDyhPoDh86WbpllIGSzVwcJYlJ4VJ) 22 | * Autograd 23 | * [PyTorch: Tensors and autograd](https://colab.research.google.com/drive/1pMlThbtxTloO2_kjVHiKSLDIWzTzwy-w) 24 | * [PyTorch: Defining New autograd Functions](https://colab.research.google.com/drive/1DYN2MTlYO4pH2nEPYSvNSZ5UeLzlBC5o) 25 | * [ TensorFlow: Static Graphs](https://colab.research.google.com/drive/1_lmbHaVqjsJLGK--qdB-8SgnBYCb_eZO) 26 | * nn module 27 | * [PyTorch: nn](https://colab.research.google.com/drive/1rapdN2TWzFlnSIAreupyp9EQyaPSLeCI) 28 | * [PyTorch: optim](https://colab.research.google.com/drive/1YjUydyfYOYdjet-Mbp-iXF7d4K5_AjUt) 29 | * [PyTorch: Custom nn Modules](https://colab.research.google.com/drive/14O9Yu1Vv7I8zywk3E1si-Zd6JPUtr6bk) 30 | * [PyTorch: Control Flow + Weight Sharing](https://colab.research.google.com/drive/1aCLvTV2miF4U5hJljNPHUzcijBtzd6BL) 31 | * [Transfer Learning Tutorial](https://colab.research.google.com/drive/1RADkS5naNGsBr_SoKL4NrjN5NphVhk_7) 32 | * [Deploying a Seq2Seq Model with the Hybrid Frontend](https://colab.research.google.com/drive/1lq9MMIpJwQP6DH7QCdvfuGJkqdUFravU) 33 | * [Saving and Loading Models](https://colab.research.google.com/drive/1F5Vk9A7q-KyT4JR8vj_ly7ySqlB-CRcq) 34 | * [What is torch.nn really?](https://colab.research.google.com/drive/1Z0dCglegggLunaqxdafiTX3nbmPYryDg) 35 | 36 | *** 37 | # Image 38 | * [Finetuning Torchvision Models](https://colab.research.google.com/drive/1_VPPbBj_92lmYBm8RwmpY2Qto3Cgweqe) 39 | * [Spatial Transformer Networks Tutorial](https://colab.research.google.com/drive/1FvxC9l-M_ZHqmfRnVHxR1siEB7FcJKXS) 40 | * [Neural Transfer Using PyTorch](https://colab.research.google.com/drive/11CGMdE7F58H0bknm7WNvdQw-5l1tgeZ_) 41 | * [Adversarial Example Generation](https://colab.research.google.com/drive/1R0rE5MfdeUhB65fr-GzMr7aDbStMuJGL) 42 | * [Transfering a Model from PyTorch to Caffe2 and Mobile using ONNX](https://colab.research.google.com/drive/1NELDQYwXwr4ZOhl77CoHK2Gv7X2coaJY)(Not fully functional) 43 | *** 44 | # Text 45 | * [Chatbot Tutorial](https://colab.research.google.com/drive/1Qs6m-gZ7It53hmMbCNGST962cycQWRvW) 46 | * [Classifying Names with a Character-Level RNN](https://colab.research.google.com/drive/1OvOe4dsd7VFymz2PE2r1BMHiJtglBeu1) 47 | * [Generating Names with a Character-Level RNN](https://colab.research.google.com/drive/165YAVmrWuuM-ESZ2ELUJahkpgH3fyTAF) 48 | * Deep Learning for NLP with Pytorch 49 | * [Introduction to PyTorch](https://colab.research.google.com/drive/13ZBvOIv5Y9TygB4eYsh1HpE7f8stF2xJ) 50 | * [Deep Learning with PyTorch](https://colab.research.google.com/drive/1EWTfj2MsPo1HjBWSLH7K0P-JuoZSkoLh) 51 | * [Word Embeddings: Encoding Lexical Semantics](https://colab.research.google.com/drive/1ZsfSsj91SVTsH8JXpPCUvTVkZFzEkCNr) 52 | * [Sequence Models and Long-Short Term Memory Networks](https://colab.research.google.com/drive/1Av0fPm6cvr5go8RTVMOV_O5YHBAMxglo) 53 | * [Advanced: Making Dynamic Decisions and the Bi-LSTM CRF](https://colab.research.google.com/drive/1IOpo97OD7Af0vQ31U9tmAWNw36tz_YK4) 54 | * [Translation with a Sequence to Sequence Network and Attention](https://colab.research.google.com/drive/1ixOr2JarQUfUL5mioVjD9QV3xpj6c36S) 55 | *** 56 | # Generative 57 | * [DCGAN Tutorial](https://colab.research.google.com/drive/1u6SekdLKZMLHXyLsJmvGnwR3CKOv8EWJ) 58 | *** 59 | # Reinforcement Learning 60 | * [Reinforcement Learning (DQN) Tutorial](https://colab.research.google.com/drive/1fQA5LK3LJvWkXAB-mvS6-rLZFbkqa9KE) 61 | *** 62 | 63 | ## Note - If the notebooks shows random text similar to following figure then open the file in colab. 64 | ![img](https://github.com/param087/Pytorch-tutorial-on-Google-colab/blob/master/Images/Screenshot%20(74).png) 65 | Best way to run the notebook is to copy it in your google drive. 66 | 67 | 68 | --------------------------------------------------------------------------------