Table of Contents

1. Introduction and Evolution of AI Technologies
2. Modern Approach to AI
3. Introduction to Machine Learning
4. Regression Versus Classification Model
5. Naive Bayes as a Linear Classifier
6. Tree-Based Machine Learning Models
7. Distance-Based Machine Learning Models
8. Support Vector Machines
9. Introduction to Artificial Neural Networks
10. Training Neural Networks
11. Introduction to Convolutional Neural Networks
12. Classification Using CNN
13. Pre-trained CNN Architectures
14. Introduction to Recurrent Neural Networks
15. Introduction to Long Short-Term Memory (LSTM)
16. Application of LSTM in NLP and TS Forecasting
17. Emerging Trends and Ethical Considerations in AI
      Index