1. Lecture 3: Linear Regression (with One Variable)

2. Supervised Learning: Regression
Right answers are given for inputs
Regression refers to predicting continuous valued output (e.g. price)

3. Notations

4. Learning Process

5. Hypothesis Representation

6. Hypothesis Representation

7. Finding Parameters

8. Cost Function

9. Cost Function Intuition

10. Cost Function Intuition (Cont)

11. Cost Function Intuition (Cont)

12. Cost Function Intuition (Cont)

13. Cost Function Intuition (Cont)

14. Cost Function Intuition (Cont)cc cc

15. Cost Function Intuition (Cont)cc cc cc

16. Cost Function Intuition (Cont)cc cc cc cc cc cc cc

17. Cost Function Intuition (Cont)cc cc cc cc cc cc cc
= 1

18. Cost Function Intuition 2

19. Cost Function Intuition 2

20. Cost Function Intuition 2 (Cont)

21. Cost Function Intuition 2 (Cont)

22. Cost Function Intuition 2 (Cont)

23. Cost Function Intuition 2 (Cont)