ekramasif / Basic-Machine-Learning

This is a repo of basic Machine Learning what I learn. More to go...

Basic Machine Learning

• This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resources.

Contents

• Introduction
• Interview Resources
• Artificial Intelligence
• Genetic Algorithms
• Resources on Kaggle
• Cheat Sheets
• Classification
• Linear Regression
• Logistic Regression
• Model Validation using Resampling
  • Cross Validation
• Deep Learning
  • Frameworks
  • Feed Forward Networks
  • Recurrent Neural Nets, LSTM, GRU
  • Restricted Boltzmann Machine, DBNs
  • Autoencoders
  • Convolutional Neural Nets
  • Graph Representation Learning
• Natural Language Processing
  • Word2Vec
• Computer Vision
• Support Vector Machine
• Reinforcement Learning
• Decision Trees
• Random Forest / Bagging
• Boosting
• Bayesian Machine Learning
• Semi Supervised Learning
• Other Useful Tutorials

Introduction

• Machine Learning Course by Andrew Ng (Stanford University)

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Contributing

Have anything in mind that you think is awesome and would fit in this list? Feel free to send me a pull request!