/ML-Notebooks

:fire: A series of code examples for all sorts of machine learning tasks and applications.

🐙 ML Notebooks

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.

Feel 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 Attention Mechanism and Positional Embeddings An implementation of Attention Mechanism and Positional Embeddings on a text classification task
Kaggle
Siamese Network An implementation of Siamese Network for finding Image Similarity
Kaggle
Variational Auto Encoder An implementation of Variational Auto Encoder to generate Augmentations for MNIST Handwritten Digits
Kaggle
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
Kaggle
Object Detection using Selective Search A basic object detection implementation using selective search on top of an image classifer
Kaggle

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}
}