In this repository you will find things related to Machine Learning. I try to make the code as clear as possible, and the goal is be to used as a learning resource and a way to lookup problems to solve specific problems. For most I have also done video explanations on youtube to make it easier to follow the code if you're a beginner, and for a few I've done the derivations on my blog. If you got any questions add an issue or would like to add an algorithm do a PR! This repository is contribution friendly 😃
✅ 🔺: Algorithm is tested/untested
Linear Regression - With Gradient Descent ✅
Linear Regression - With Normal Equation ✅
Logistic Regression
Naive Bayes - Gaussian Naive Bayes
K-nearest neighbors
K-means clustering
Support Vector Machine - Using CVXOPT
Neural Network
Always looking to make this resource larger and if you have any suggestions leave them as a comment on YouTube.
Tensor Basics
Feedforward Neural Network
Convolutional Neural Network
Recurrent Neural Network
Bidirectional Recurrent Neural Network
Loading and saving model
Custom Dataset (Images)
Custom Dataset (Text)
Transfer Learning and finetuning
Transforms & Data Augmentation
Learning Rate Scheduler
Initialization of weights
Calculate Mean and STD of Images
Image Captioning
Neural Style Transfer
Generative Adversarial Networks
Torchtext [1] Torchtext [2] Torchtext [3]
Seq2Seq - Sequence to Sequence (LSTM)
Seq2Seq + Attention - Sequence to Sequence with Attention (LSTM)
Seq2Seq Transformers - Sequence to Sequence with Transformers
Transformers from scratch - Attention Is All You Need
LeNet5 - CNN architecture
VGG - CNN architecture
Inception v1 - CNN architecture
ResNet - CNN architecture
- Exploring MNIST - Needs updating
Text Generating LSTM