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
Counterfactual Explanations	A basic tutorial to learn about counterfactual explanations for explainable AI
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.

Name	Description	Notebook
Bag of Words Text Classifier	Build a simple bag of words text classifier.
Continuous Bag of Words (CBOW) Text Classifier	Build a continuous bag of words text classifier.
Deep Continuous Bag of Words (Deep CBOW) Text Classifier	Build a deep continuous bag of words text classifier.
Text Data Augmentation	An introduction to the most commonly used data augmentation techniques for text and their implementation
Emotion Classification with Fine-tuned BERT	Emotion classification using fine-tuned BERT model

Name	Description	Notebook
Text Classification using Transformer	An implementation of Attention Mechanism and Positional Embeddings on a text classification task
Neural Machine Translation using Transformer	An implementation of Transformer to translate human readabke dates in any format to YYYY-MM-DD format.
Feature Tokenizer Transformer	An implementation of Feature Tokenizer Transformer on a classification task
Named Entity Recognition using Transformer	An implementation of Transformer to perform token classification and identify species in PubMed abstracts
Extractive Question Answering using Transformer	An implementation of Transformer to perform extractive question answering

Name	Description	Notebook
Siamese Network	An implementation of Siamese Network for finding Image Similarity
Variational Auto Encoder	An implementation of Variational Auto Encoder to generate Augmentations for MNIST Handwritten Digits
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
Object Detection using Selective Search	A basic object detection implementation using selective search on top of an image classifer

Name	Description	Notebook
Deep Convolutional GAN	An Implementation of Deep Convolutional GAN to generate MNIST digits
Wasserstein GAN with Gradient Penalty	An Implementation of Wasserstein GAN with Gradient Penalty to generate MNIST digits
Conditional GAN	An Implementation of Conditional GAN to generate MNIST digits

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}
}