Machine Learning and Artificial Intelligence

1. to Machine Learning (ML) and Artificial Intelligence (AI).

2. Taxonomy, Regression, clustering.

3. Supervised Learning.

4. Unsupervised Learning.

5. Reinforcement Learning.

6. Decission trees.

7. Fuzzy Logic.

8. Support vector machines.

9. Bayes – rule Learning.

10. Artificial Neuron Networks – Deep Learning Networks.

11. Evaluation of the models.