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 ✅
Logistic Regression
Naive Bayes - Gaussian Naive Bayes
K-nearest neighbors
K-means clustering
Support Vector Machine - Using CVXOPT
Neural Network
- Decision Tree
If you have any specific video suggestion please make 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
Data augmentation using Torchvision
Data augmentation using Albumentations
TensorBoard Example
Calculate Mean and STD of Images
Simple Progress bar
Deterministic Behavior
Learning Rate Scheduler
Initialization of weights
Text Generating LSTM
Semantic Segmentation w. U-NET
Image Captioning
Neural Style Transfer
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
Intersection over Union
Non-Max Suppression
Mean Average Precision
YOLOv1 from scratch
YOLOv3 from scratch
LeNet5 - CNN architecture
VGG - CNN architecture
Inception v1 - CNN architecture
ResNet - CNN architecture
EfficientNet - CNN architecture
If you have any specific video suggestion please make a comment on YouTube :)
Tutorial 1 - Installation, Video Only
Tutorial 2 - Tensor Basics
Tutorial 3 - Neural Network
Tutorial 4 - Convolutional Neural Network
Tutorial 5 - Regularization
Tutorial 6 - RNN, GRU, LSTM
Tutorial 7 - Functional API
Tutorial 8 - Keras Subclassing
Tutorial 9 - Custom Layers
Tutorial 10 - Saving and Loading Models
Tutorial 11 - Transfer Learning
Tutorial 12 - TensorFlow Datasets
Tutorial 13 - Data Augmentation
Tutorial 14 - Callbacks
Tutorial 15 - Custom model.fit
Tutorial 16 - Custom Loops
Tutorial 17 - TensorBoard
Tutorial 18 - Custom Dataset Images
Tutorial 19 - Custom Dataset Text
Tutorial 20 - Classifying Skin Cancer - Beginner Project Example