Learn Python from Scratch for Data Analysis & Machine Learning – linear regression and t-test
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1. How to install Python
2. How to run code in Spyder and Colab (02:25)
3. Assign and print variables (04:20)
4. Data types in Python (05:30)
5. How to import and use a module - math module (08:00)
6. List and tuple (11:30)
7. Create vectors and matrices in NumPy (12:40)
8. Index in an array (13:12)
9. Reshape an array (15:50)
10. Mean and standard deviation (22:00)
11. Create a scatter plot (22:48)
12. Functions vs method (22:47)
13. Linear regression with scipy (25:00)
14. Linear regression with scikit-learn (28:35)
15. Create an instance of a class (29:55)
16. Sum of squared error, SSE (34:50)
17. R2 value (35:37)
18. Training data and test data (36:00)
19. Linear regression with statsmodels (39:20)
20. t-test (40:18)
21. Import data from an Excel file with pandas (41:19)
22. Boxplot, histogram and pie chart (44:35)
23. Multiple linear regression (47:20)