Outline
Practical Data Science and Machine Learning: A Comprehensive Guide
From Fundamental Concepts to Advanced Techniques and Real-world Applications
1. Introduction
2. Data Science - Overview
3. Data Science Ecosystem
4. Introduction to Python for Data Science
5. Essential Mathematics for Machine Learning
6. The fundamentals of Machine learning
7. Supervised learning
8. Unsupervised learning
9. Introduction to Deep Learning
10. Convolutional Neural Networks (CNN)
11. Recurrent Neural Networks (RNN)
12. Transformers
13. Natural Language Processing
14. Computer vision
15. Time Series Forecasting
16. Recommender Systems
17. Productionizing Machine Learning Models
18. End to End Real-World Projects
19. Bonus - Flash Cards
20. Bonus - Mobile APP
Content Notice 🔄
Please note that the content of this course is subject to continuous review and updates 💡. Stay engaged 🎓.