LINEAR REGRESSION & Model Pipeline | Machine Learning Practices | Session - 8

Linear Regression & Model Pipeline | Machine Learning Practices | Session - 8
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In this session, we've covered:-
- Linear Regression from Scratch
- Preprocessing
- ColumnTransformer
- Feature Union
- Model Pipeline
- Linear Regression (Explanation)
- Cost Function - Mean Squared Error
- Gradient Descent
- Linear Regression from Scratch
Kaggle notebook 🔼 (Make sure to upvote them):
Notebook 1: Model Pipeline
www.kaggle.com/code/param302/...
Notebook 2: Linear Regression with 3d Interactive Plots
www.kaggle.com/code/param302/...
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Chapters:
00:00 Overview & Setup
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Bio link 🔗 param302.bio.link
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LinkedIn 🔗 / param302
Github 🔗 github.com/Param302
Kaggle 🔗 kaggle.com/param302

[@virus_suriv-ut4mh]

Excellent Work! You really teach very nice.

[@Param3021]

Thank you 🙏

[@AmitojSinghMiglani]

Great work !

[@Param3021]

Thank you 🙏

[@vishaIll]

thoda awaz increase plz

[@Param3021]

@@vishaIll from session 10, it's increased