Basic Statistics & Regression for Machine Learning in Python Online Course & PDF Guides

Price: 10.00 USD | Size: 9.2 GB | Duration : 5 +  Hours | 63 Video Lessons | ★★★★★ 4.6

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Basic Statistics & Regression for Machine Learning in Python Online Course & PDF Guides

 A quick and easy guide on statistical regression for machine learning 

 

What you'll learn

• Python Basics, Statistics and Regression behind Machine Learning in Python and also using Manual Calculations

Course Contents

PART-01

01.01-course introduction and table of contents

02.01-environment setup-part 1

02.02-environment setup-part 2

03.01-essential components included in anaconda

04.01-python basics-assignment

05.01-python basics-flow control-part 1

05.02-python basics-flow control-part 2

06.01-python basics-list and tuples

07.01-python basics-dictionary and functions-part 1

07.02-python basics-dictionary and functions-part 2

08.01-numpy basics-part 1

08.02-numpy basics-part 2

09.01-matplotlib basics-part 1

09.02-matplotlib basics-part 2

10.01-basics of data for machine learning

11.01-central data tendency-mean

12.01-central data tendency-median and mode-part 1

12.02-central data tendency-median and mode-part 2

13.01-variance and standard deviation manual calculation-part 1

13.02-variance and standard deviation manual calculation-part 2

14.01-variance and standard deviation using python

PART-02

15.01-percentile manual calculation

16.01-percentile using python

17.01-uniform distribution

18.01-normal distribution-part 1

18.02-normal distribution-part 2

19.01-manual z score calculation

20.01-z-score calculation using python

21.01-multi variable dataset scatter plot

22.01-introduction to linear regression

23.01-manually finding linear regression correlation coefficient-part 1

23.02-manually finding linear regression correlation coefficient-part 2

24.01-manually finding linear regression slope equation-part 1

24.02-manually finding linear regression slope equation-part 2

25.01-manually predicting the future value using equation

26.01-linear regression using python introduction

27.01-linear regression using python-part 1

27.02-linear regression using python-part 2

28.01-strong and weak linear regression

29.01-predicting future value using linear regression in python

30.01-polynomial regression introduction

31.01-polynomial regression visualization

32.01-polynomial regression prediction and r2 value

33.01-polynomial regression finding sd components

PART-03

34.01-polynomial regression manual method equations

35.01-finding sd components for abc

36.01-finding abc

37.01-polynomial regression equation and prediction

38.01-polynomial regression coefficient

39.01-multiple regression introduction

40.01-multiple regression using python-data import as csv

41.01-multiple regression using python-data visualization

42.01-creating multiple regression object and prediction using python

43.01-manual multiple regression-intro and finding means

44.01-manual multiple regression-finding components-part 1

44.02-manual multiple regression-finding components-part 2

45.01-manual multiple regression-finding abc

46.01-manual multiple regression equation prediction and coefficients

47.01-feature scaling introduction

48.01-standardization scaling using python-part 1

48.02-standardization scaling using python-part 2

49.01-standardization scaling using manual calculation-part 1

49.02-standardization scaling using manual calculation-part 2

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