In this repository I will be uploading everything machine learning related. 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
Everything for now is implemented using the PyTorch-framework.
- Tensor Basics
- Feedforward Neural Network
- Convolutional Neural Network
- Recurrent Neural Network
- Bidirectional Recurrent Neural Network
- Loading and saving model
- Custom Dataset (Images)
- Transfer Learning and finetuning
- Transforms & Data Augmentation
- Learning Rate Scheduler
- Initialization of weights
- 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