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