Machine Learning From Scratch

This is a personal side project that I am working on. I am trying to implement some machine learning algorithms from scratch.

GitHub Repository

iThome 30 Days

Every algorithm has three parts:

• Using the algorithm to solve a problem with libraries
• Using the algorithm to solve a problem without libraries (from scratch)
• Using the algorithm to solve a real-world problem

Algorithms

• Supervised Learning
  • Polynomial Regression Titanic - Machine Learning from Disaster
  • Naive Bayes Digit Recognizer
  • Support Vector Machine House Prices - Advanced Regression Techniques
• Unsupervised
  • KNN Spaceship Titanic
  • Gaussian Mixture Model Mall Customer Segmentation Data
  • Autoencoder Labelled Faces in the Wild (LFW) Dataset

• Multilayer Perceptron

• NN
  • Neural Network Natural Language Processing with Disaster Tweets
  • Recurrent Neural Network Store Sales - Time Series Forecasting
• RL
  • Deep Q-Network REINFORCEMENT LEARNING (DQN) TUTORIAL

References

• Machine Learning from Scratch