This repository is intended for basic Artificial Intelligence algorithms that can be used as models.
Some implementations have been taken from online courses such as "Machine Learning A-Z โข: Hands-On Python and R In Data Science" (from SuperDataScience).
The folder sequence expected:
- Atificial Intelligence
- Machine Learning
- Supervised Learning
- Unsupervised Learning
- Clustering
- Association Rule Learning
- Dimensionality Reduction
- Ensemble Learning (Basics)
- Stacking
- Bagging
- Boosting
- Reinforcement Learning
- Neural Networks and Deep Learning
- Convolutional Neural Networks
- Recurrent Neural Networks (Fix repository)
- Generative Adversarial Networks
- Autoencoders (Next addition)
- Perceptrons
- Extreme Learning Machines
- Search Agents
- Machine Learning