A series of code examples for all sorts of machine learning tasks and applications.
The notebooks are meant to be minimal and easily reusable and extendable.
You are free to use them for educational and research purposes.
Name |
Description |
Notebook |
Introduction to Computational Graphs |
A basic tutorial to learn about computational graphs |
|
PyTorch Hello World! |
Build a simple neural network and train it |
|
A Gentle Introduction to PyTorch |
A detailed explanation introducing PyTorch concepts |
|
Logistic Regression from Scratch |
An implementation of logistic regression from scratch |
|
Concise Logistic Regression |
Concise implementation of logistic regression model for binary image classification. |
|
First Neural Network - Image Classifier |
Build a minimal image classifier using MNIST |
|
Neural Network from Scratch |
An implementation of simple neural network from scratch |
|
Introduction to GNNs |
Introduction to Graph Neural Networks. Applies basic GCN to Cora dataset for node classification. |
|
Emotion Classification with Fine-tuned BERT |
Emotion classification using fine-tuned BERT model |
|
Text Classification using Transformer |
An implementation of Attention Mechanism and Positional Embeddings on a text classification task |
![Open in Kaggle Kaggle](https://camo.githubusercontent.com/1398db766d8ca60e6f296aac9ac429e344705c6c2c7e1ceb024230aac69fd6be/68747470733a2f2f6b6167676c652e636f6d2f7374617469632f696d616765732f6f70656e2d696e2d6b6167676c652e737667) |
Siamese Network |
An implementation of Siamese Network for finding Image Similarity |
![Open in Kaggle Kaggle](https://camo.githubusercontent.com/1398db766d8ca60e6f296aac9ac429e344705c6c2c7e1ceb024230aac69fd6be/68747470733a2f2f6b6167676c652e636f6d2f7374617469632f696d616765732f6f70656e2d696e2d6b6167676c652e737667) |
Variational Auto Encoder |
An implementation of Variational Auto Encoder to generate Augmentations for MNIST Handwritten Digits |
![Open in Kaggle Kaggle](https://camo.githubusercontent.com/1398db766d8ca60e6f296aac9ac429e344705c6c2c7e1ceb024230aac69fd6be/68747470733a2f2f6b6167676c652e636f6d2f7374617469632f696d616765732f6f70656e2d696e2d6b6167676c652e737667) |
Object Detection using Sliding Window and Image Pyramid |
A basic object detection implementation using sliding window and image pyramid on top of an image classifer |
![Open in Kaggle Kaggle](https://camo.githubusercontent.com/1398db766d8ca60e6f296aac9ac429e344705c6c2c7e1ceb024230aac69fd6be/68747470733a2f2f6b6167676c652e636f6d2f7374617469632f696d616765732f6f70656e2d696e2d6b6167676c652e737667) |
Object Detection using Selective Search |
A basic object detection implementation using selective search on top of an image classifer |
![Open in Kaggle Kaggle](https://camo.githubusercontent.com/1398db766d8ca60e6f296aac9ac429e344705c6c2c7e1ceb024230aac69fd6be/68747470733a2f2f6b6167676c652e636f6d2f7374617469632f696d616765732f6f70656e2d696e2d6b6167676c652e737667) |
Neural Machine Translation using Transformer |
An implementation of Transformer to translate human readabke dates in any format to YYYY-MM-DD format. |
![Open in Kaggle Kaggle](https://camo.githubusercontent.com/1398db766d8ca60e6f296aac9ac429e344705c6c2c7e1ceb024230aac69fd6be/68747470733a2f2f6b6167676c652e636f6d2f7374617469632f696d616765732f6f70656e2d696e2d6b6167676c652e737667) |
Feature Tokenizer Transformer |
An implementation of Feature Tokenizer Transformer on a classification task |
![Open in Kaggle Kaggle](https://camo.githubusercontent.com/1398db766d8ca60e6f296aac9ac429e344705c6c2c7e1ceb024230aac69fd6be/68747470733a2f2f6b6167676c652e636f6d2f7374617469632f696d616765732f6f70656e2d696e2d6b6167676c652e737667) |
Counterfactual Explanations |
A basic tutorial to learn about counterfactual explanations for explainable AI |
|
If you find any bugs or have any questions regarding these notebooks, please open an issue. We will address it as soon as we can.
Reach out on Twitter if you have any questions.
Please cite the following if you use the code examples in your research:
@misc{saravia2022ml,
title={ML Notebooks},
author={Saravia, Elvis and Rastogi, Ritvik},
journal={https://github.com/dair-ai/ML-Notebooks},
year={2022}
}