In this repository you will find tutorials and projects 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 if you want a walkthrough for the code. If you got any questions or suggestions for future videos I prefer if you ask it on YouTube. This repository is contribution friendly, so if you feel you want to add something then I'd happily merge a PR 😃
-  Linear Regression - With Gradient Descent ✅
-  Linear Regression - With Normal Equation ✅
- Â Logistic Regression
- Â Naive Bayes - Gaussian Naive Bayes
- Â K-nearest neighbors
- Â K-means clustering
- Â Support Vector Machine - Using CVXOPT
- Â Neural Network
- Decision Tree
If you have any specific video suggestion please make a comment on YouTube :)
- Â Tensor Basics
- Â Feedforward Neural Network
- Â Convolutional Neural Network
- Â Recurrent Neural Network
- Â Bidirectional Recurrent Neural Network
- Â Loading and saving model
- Â Custom Dataset (Images)
- Â Custom Dataset (Text)
- Â Mixed Precision Training
- Â Imbalanced dataset
- Â Transfer Learning and finetuning
- Â Data augmentation using Torchvision
- Â Data augmentation using Albumentations
- Â TensorBoard Example
- Â Calculate Mean and STD of Images
- Â Simple Progress bar
- Â Deterministic Behavior
- Â Learning Rate Scheduler
- Â Initialization of weights
- Â Text Generating LSTM
- Â Semantic Segmentation w. U-NET
- Â Image Captioning
- Â Neural Style Transfer
- Â Torchtext [1] Torchtext [2] Torchtext [3]
- Â Seq2Seq - Sequence to Sequence (LSTM)
- Â Seq2Seq + Attention - Sequence to Sequence with Attention (LSTM)
- Â Seq2Seq Transformers - Sequence to Sequence with Transformers
- Â Transformers from scratch - Attention Is All You Need
- Â Intersection over Union
- Â Non-Max Suppression
- Â Mean Average Precision
- Â YOLOv1 from scratch
- Â YOLOv3 from scratch
- Â Simple FC GAN
- Â DCGAN
- Â WGAN
- Â WGAN-GP
- Â Pix2Pix
- Â CycleGAN
- Â ProGAN
- SRGAN
- ESRGAN
- StyleGAN - NOTE: NOT DONE
- Â LeNet5 - CNN architecture
- Â VGG - CNN architecture
- Â Inception v1 - CNN architecture
- Â ResNet - CNN architecture
- Â EfficientNet - CNN architecture
If you have any specific video suggestion please make a comment on YouTube :)
- Â Tutorial 1 - Installation, Video Only
- Â Tutorial 2 - Tensor Basics
- Â Tutorial 3 - Neural Network
- Â Tutorial 4 - Convolutional Neural Network
- Â Tutorial 5 - Regularization
- Â Tutorial 6 - RNN, GRU, LSTM
- Â Tutorial 7 - Functional API
- Â Tutorial 8 - Keras Subclassing
- Â Tutorial 9 - Custom Layers
- Â Tutorial 10 - Saving and Loading Models
- Â Tutorial 11 - Transfer Learning
- Â Tutorial 12 - TensorFlow Datasets
- Â Tutorial 13 - Data Augmentation
- Â Tutorial 14 - Callbacks
- Â Tutorial 15 - Custom model.fit
- Â Tutorial 16 - Custom Loops
- Â Tutorial 17 - TensorBoard
- Â Tutorial 18 - Custom Dataset Images
- Â Tutorial 19 - Custom Dataset Text
- Â Tutorial 20 - Classifying Skin Cancer - Beginner Project Example