1. Introduction to Supervised Learning Algorithms
2. Types of Variables
3. Data Types.html
4. Introduction to Regression Analysis
5. Regression Model.html
6. Regression Model Slope
7. Regression Slope.html
8. The Intercept Value
9. The Intercept Value.html
10. R-Squared Value
11. P-Value
12. Simple Linear Regression
13. Concepts used in Machine Learning (Important).html
14.1 Study_Hours.csv
14. Overview on the dataset
15.1 simple linear regression.zip
15. Create Simple Linear Regression Model in Python-Part 1
16. Create Simple Linear Regression Model in Python-Part 2
17. Create Simple Linear Regression Model in Python-Part 3
18. Create Simple Linear Regression Model in Python-Part 4
19. Create Simple Linear Regression Model in Python-Part 5
20. Multiple Linear Regression
21. Dummy Variables
22. Dummy Variables Trap.html
23. Stepwise Approach
24. Assumptions of Multiple Linear Regression
25.1 Companies spends and profits.csv
25. Overview on the business problem data
26.1 multiple linear regression.zip
26. Create Multiple Linear Regression Model in Python-Part 1
27. Create Multiple Linear Regression Model in Python-Part 2
28. Create Multiple Linear Regression Model in Python-Part 3
29. Create Multiple Linear Regression Model in Python-Part 4
30. Polynomial Regression
31.1 Reward_system.csv
31. Overview on the business problem data
32.1 polynomial regression model.zip
32. Create Polynomial Regression Model in Python-Part 1
33. Create Polynomial Regression Model in Python-Part 2
34. Create Polynomial Regression Model in Python-Part 3
35. Course Rating.html
36. Introduction to Classification
37. Introduction to Logistic Regression
38. Confusion Matrix
39. Standard Scaler
40.1 Bank_Data.csv
40. Overview on the business problem data
41.1 logistic regression model.zip
41. Create Logistic Regression Model in Python-Part 1
42. Create Logistic Regression Model in Python-Part 2
43. KNN Classification Algorithm
44.1 Bank_Data.csv
44.2 knn model.zip
44. Create KNN Model in Python
45. Support Vector Machine (SVM) Classification Algorithm
46.1 support vector machine.zip
46. Create Support Vector Machine in Python
47. Naive Bayes Algorithm Part 1
48. Naive Bayes Algorithm Part 2
49.1 naive bayes model.zip
49. Create Naive Bayes Model in Python
50. Decision Tree Algorithm
51.1 Bank_Data.csv
51.2 decision tree model .zip
51. Create Decision Tree Model in Python
52. Random Forest Algorithm
53.1 random forest model.zip
53. Create Random Forest Model in Python
54. Course Rating.html
