๐๐ถ๐ฐ๐ธ๐๐๐ฎ๐ฟ๐๐ถ๐ป๐ด ๐ฌ๐ผ๐๐ฟ ๐ ๐ ๐๐ผ๐๐ฟ๐ป๐ฒ๐ ๐๐ถ๐๐ต ๐ฎ ๐ฆ๐ผ๐น๐ถ๐ฑ ๐๐ผ๐๐ป๐ฑ๐ฎ๐๐ถ๐ผ๐ป ๐ถ๐ป ๐๐ถ๐ป๐ฒ๐ฎ๐ฟ ๐ฅ๐ฒ๐ด๐ฟ๐ฒ๐๐๐ถ๐ผ๐ป
๐๐ถ๐ป๐ฒ๐ฎ๐ฟ ๐ฟ๐ฒ๐ด๐ฟ๐ฒ๐๐๐ถ๐ผ๐ป is often the first algorithm every beginner encounters in the ๐ท๐ผ๐๐ฟ๐ป๐ฒ๐ ๐ผ๐ณ ๐ ๐ฎ๐ฐ๐ต๐ถ๐ป๐ฒ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด. But simply understanding the gradient function isn't enoughโbuilding a strong foundation requires an in-depth study of the interconnected concepts.
To help you get started, hereโs a comprehensive series of lectures designed to make your ML fundamentals robust. Delivered in Hindi and explained on a whiteboardโ๐ซ๐ถ๐ด๐ต ๐ญ๐ช๐ฌ๐ฆ ๐ถ๐ฏ๐ช๐ท๐ฆ๐ณ๐ด๐ช๐ต๐บ ๐ค๐ญ๐ข๐ด๐ด๐ณ๐ฐ๐ฐ๐ฎ๐ดโthese lectures provide a structured, deep-dive approach to learning:
1. Quartile & Box Plot:
2. Loss function and Gradient descent:
3. Concept of linear regression and R2 score:
4. Assumptions of Linear Regression:
5. Multicollinearity and VIF:
6. Polynomial regression:
7. L1 L2 Regularization:
8. Hyoeroarameter Tuning:
9. K-Fold cross validation:
10. Encoding categorical variable:
11. Interview preparation:
12. End-to-end project:
๐ฅ Each lecture is 45 minutes to 1 hour long and dives deep into the concepts to strengthen your ML foundation.
This series is just the beginning! Upcoming videos will cover classification, clustering, natural language processing, and more advanced topics.
๐ก Remember: Learning Machine Learning and AI should never be limited by language barriers.
Dive into this lecture series to make your ML fundamentals unshakable. Letโs build a strong foundation for your AI journey together!
#LinearRegression #MachineLearning #DataScience #AIInHindi #MLBasics #LearningJourney
Very informative sessions...