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https://github.com/param087/Pytorch-tutorial-on-Google-colab

PyTorch Tutorial on google colaboratory.
https://github.com/param087/Pytorch-tutorial-on-Google-colab

Last synced: 3 months ago
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PyTorch Tutorial on google colaboratory.

Host: GitHub
URL: https://github.com/param087/Pytorch-tutorial-on-Google-colab
Owner: param087
Created: 2019-01-17T05:27:48.000Z (almost 6 years ago)
Default Branch: master
Last Pushed: 2019-09-11T10:35:02.000Z (over 5 years ago)
Last Synced: 2024-06-23T01:45:02.324Z (6 months ago)
Homepage:
Size: 235 KB
Stars: 75
Watchers: 3
Forks: 17
Open Issues: 0
Metadata Files:
- Readme: Readme.md

Awesome Lists containing this project

README

        # PyTorch tutorial on google colab notebook 

Some notebook contains the installation command for PyTorch but now google colab have pytorch pre-install.

### [reference - https://pytorch.org/tutorials/](https://pytorch.org/tutorials/)

***

## Requirements - Chrome Browser and Google drive login

                  

 

***

# Getting Started

  * Deep Learning with PyTorch: A 60 Minute Blitz

    * [What is PyTorch?](https://colab.research.google.com/drive/1SCW0WNW4716jV803YJiRvsvcQezR0Tzx)

    * [Autograd: Automatic Differentiation](https://colab.research.google.com/drive/1XW3phQbownypM9xyG0_05hzxVe5lc1Yr)

    * [Neural Networks](https://colab.research.google.com/drive/1kYBwZfxC-L7dvj51NcNdS1VSQPT0IjqG)

    * [Training a Classifier](https://colab.research.google.com/drive/1v-rWBOFdqfBRaNcx27uC9q82K9XrXjHx)

    * [Optional: Data Parallelism](https://colab.research.google.com/drive/1e6FRN2YKSJlefWrZKPp4Hy-n5l9ckhC-)

 * [Data Loading and Processing Tutorial](https://colab.research.google.com/drive/13BxH3nkqwlU_ZCplU2Czn8cgP7nnR0xR)

 * Learning PyTorch with Examples

    * Tensors

        * [Warm-up: numpy](https://colab.research.google.com/drive/1uT6cq0JQZBhw4M0EJZUoikekES2ltNGw)

        * [PyTorch: Tensors](https://colab.research.google.com/drive/16GkGDyhPoDh86WbpllIGSzVwcJYlJ4VJ)

    * Autograd

        * [PyTorch: Tensors and autograd](https://colab.research.google.com/drive/1pMlThbtxTloO2_kjVHiKSLDIWzTzwy-w)

        * [PyTorch: Defining New autograd Functions](https://colab.research.google.com/drive/1DYN2MTlYO4pH2nEPYSvNSZ5UeLzlBC5o)

        * [ TensorFlow: Static Graphs](https://colab.research.google.com/drive/1_lmbHaVqjsJLGK--qdB-8SgnBYCb_eZO)

    * nn module

        * [PyTorch: nn](https://colab.research.google.com/drive/1rapdN2TWzFlnSIAreupyp9EQyaPSLeCI)

        * [PyTorch: optim](https://colab.research.google.com/drive/1YjUydyfYOYdjet-Mbp-iXF7d4K5_AjUt)

        * [PyTorch: Custom nn Modules](https://colab.research.google.com/drive/14O9Yu1Vv7I8zywk3E1si-Zd6JPUtr6bk)

        * [PyTorch: Control Flow + Weight Sharing](https://colab.research.google.com/drive/1aCLvTV2miF4U5hJljNPHUzcijBtzd6BL)

  * [Transfer Learning Tutorial](https://colab.research.google.com/drive/1RADkS5naNGsBr_SoKL4NrjN5NphVhk_7)

  * [Deploying a Seq2Seq Model with the Hybrid Frontend](https://colab.research.google.com/drive/1lq9MMIpJwQP6DH7QCdvfuGJkqdUFravU)

  * [Saving and Loading Models](https://colab.research.google.com/drive/1F5Vk9A7q-KyT4JR8vj_ly7ySqlB-CRcq)

  * [What is torch.nn really?](https://colab.research.google.com/drive/1Z0dCglegggLunaqxdafiTX3nbmPYryDg)

  

***

# Image

  * [Finetuning Torchvision Models](https://colab.research.google.com/drive/1_VPPbBj_92lmYBm8RwmpY2Qto3Cgweqe)

  * [Spatial Transformer Networks Tutorial](https://colab.research.google.com/drive/1FvxC9l-M_ZHqmfRnVHxR1siEB7FcJKXS)

  * [Neural Transfer Using PyTorch](https://colab.research.google.com/drive/11CGMdE7F58H0bknm7WNvdQw-5l1tgeZ_)

  * [Adversarial Example Generation](https://colab.research.google.com/drive/1R0rE5MfdeUhB65fr-GzMr7aDbStMuJGL)

  * [Transfering a Model from PyTorch to Caffe2 and Mobile using ONNX](https://colab.research.google.com/drive/1NELDQYwXwr4ZOhl77CoHK2Gv7X2coaJY)(Not fully functional)

***

# Text

  * [Chatbot Tutorial](https://colab.research.google.com/drive/1Qs6m-gZ7It53hmMbCNGST962cycQWRvW)

  * [Classifying Names with a Character-Level RNN](https://colab.research.google.com/drive/1OvOe4dsd7VFymz2PE2r1BMHiJtglBeu1)

  * [Generating Names with a Character-Level RNN](https://colab.research.google.com/drive/165YAVmrWuuM-ESZ2ELUJahkpgH3fyTAF)

  * Deep Learning for NLP with Pytorch

    * [Introduction to PyTorch](https://colab.research.google.com/drive/13ZBvOIv5Y9TygB4eYsh1HpE7f8stF2xJ)

    * [Deep Learning with PyTorch](https://colab.research.google.com/drive/1EWTfj2MsPo1HjBWSLH7K0P-JuoZSkoLh)

    * [Word Embeddings: Encoding Lexical Semantics](https://colab.research.google.com/drive/1ZsfSsj91SVTsH8JXpPCUvTVkZFzEkCNr)

    * [Sequence Models and Long-Short Term Memory Networks](https://colab.research.google.com/drive/1Av0fPm6cvr5go8RTVMOV_O5YHBAMxglo)

    * [Advanced: Making Dynamic Decisions and the Bi-LSTM CRF](https://colab.research.google.com/drive/1IOpo97OD7Af0vQ31U9tmAWNw36tz_YK4)

  * [Translation with a Sequence to Sequence Network and Attention](https://colab.research.google.com/drive/1ixOr2JarQUfUL5mioVjD9QV3xpj6c36S)

***

# Generative

  * [DCGAN Tutorial](https://colab.research.google.com/drive/1u6SekdLKZMLHXyLsJmvGnwR3CKOv8EWJ)

***

# Reinforcement Learning

  * [Reinforcement Learning (DQN) Tutorial](https://colab.research.google.com/drive/1fQA5LK3LJvWkXAB-mvS6-rLZFbkqa9KE)

***

## Note - If the notebooks shows random text similar to following figure then open the file in colab.

![img](https://github.com/param087/Pytorch-tutorial-on-Google-colab/blob/master/Images/Screenshot%20(74).png)

Best way to run the notebook is to copy it in your google drive.