LASSO (L1) vs Ridge (L2) vs Elastic Net Regularization in Python | Machine Learning

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LASSO (Least Absolute Shrinkage and Selection Operator) is also called L1 regularization, and Ridge is also called L2 regularization. Elastic Net is the combination of LASSO and Ridge. All three are techniques commonly used in machine learning to correct overfitting.

In this tutorial, we will cover

👉 What's the difference between LASSO (L1), Ridge (L2), and Elastic Net?
👉 How to run LASSO for classification model using Python sklearn?
👉 How to run Ridge for classification model using Python sklearn?
👉 How to run Elastic Net for classification model using Python sklearn?
👉 How to compare the performance of LASSO, Ridge, and Elastic Net?

⏰ Timecodes ⏰
0:00 - Intro
0:42 - Step 0: LASSO (L1) Vs Ridge (L2) Vs. Elastic Net
2:20 - Step 1: Import Libraries
2:57 - Step 2: Read Data
3:25 - Step 3: Train Test Split
3:42 - Step 4: Standardization
4:55 - Step 5: Logistic Regression With No Regularization
6:43 - Step 6: LASSO
8:05 - Step 7: Ridge
9:22 - Step 8: Elastic Net
10:21 - Summary

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🔥 Check out more machine learning tutorials on my website!

#lasso #regularization #machinelearning #datascience #grabngoinfo
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  2. Grab N Go Info
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  4. data science
  5. deep learning
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