Навчальна програма

1. Introduction into data science
2. numpy review
3. pandas review
4. Linerar regression
5. Ridge and Polynomial Regression
6. Logistic regression
7. Other ML models
8. Spam classification
9. Classic Neural networks
10. Multi-class classification
11. Error analiysis and evaluation metrics
12. Unsupervised learning: clustering
13. Unsupervised learning: PCA
14. sclearn review
15. Classification task using sklearn
16. Optimization algorithms and parameters
17. Regular expression
18. Sentiment analisis using nltk
19. Deep neural networks
20. tensorflow review
21. Classification task using tensorflow
22. Ssequence models: language model
23. keras review
24. Sequence models: neural machine translation
25. Knowledge transfer: word embedding
26. Computer vision
27. Google cloud platform review
28. Amazon sagemaker review