Price: 10.00 USD | Size: 9.2 GB | Duration : 5 + Hours | 63 Video Lessons | ★★★★★ 4.6
BRAND : Expert TRAINING | ENGLISH | INSTANT DOWNLOAD
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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