Book Content
chapters • 17h24m total length
1. A Gentle Introduction to Machine Learning
2. Important Elements in Machine Learning
3. Feature Selection and Feature Engineering
4. Regression Algorithms
5. Linear Classification Algorithms
6. Naive Bayes and Discriminant Analysis
7. Support Vector Machines
8. Decision Trees and Ensemble Learning
9. Clustering Fundamentals
10. Advanced Clustering
11. Hierarchical Clustering
12. Introducing Recommendation Systems
13. Introducing Natural Language Processing
14. Topic Modeling and Sentiment Analysis in NLP
15. Introducing Neural Networks
16. Advanced Deep Learning Models
17. Creating a Machine Learning Architecture
