Machine Learning Tutorial Python - 3: Linear Regression Multiple Variables
In this machine learning tutorial with python, we will write python code to predict home prices using multiple variable linear regression in python (using sklearn linear_model). Home prices are dependent on 3 independent variables: area, bedrooms and age. Pandas dataframe is used to fill missing values first and then use that dataset to train a multivariate regression model.You can use exercise at the end to consolidate your understanding on whatever you have learnt in this machine learning tutorial.
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Code: https://github.com/codebasics/py/blob/master/ML/2_linear_reg_multivariate/2_linear_regression_multivariate.ipynb
(Exercise is at the end of the ipynb notebook so just open that file and read through)
Exercise solution: https://github.com/codebasics/py/blob/master/ML/2_linear_reg_multivariate/Exercise/exercise_answer.ipynb
Topics that are covered in this Machine Learning Video:
0:00 Linear Regression With Multiple Variables:
0:48 Data set
2:07 Linear Equation
3:28 Load Data in Pandas Data Frame
4:16 Data preeprocessing (Handle Missing Values)
6:17 Train Lemear Model
8:18 Predict home prices using trained model
11:35 Exercise to predict hired candidates salary based on few parameters
Topic Highlights:
1) Data Preprocessing Handle Missing Values
2) Linear Regression Using Multiple Variables
3) Train Lemear Model
4) Exercise to predict hired candidates salary based on few parameters
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Chapters (8)
Linear Regression With Multiple Variables:
0:48
Data set
2:07
Linear Equation
3:28
Load Data in Pandas Data Frame
4:16
Data preeprocessing (Handle Missing Values)
6:17
Train Lemear Model
8:18
Predict home prices using trained model
11:35
Exercise to predict hired candidates salary based on few parameters
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Tutor Explanation
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