LINEAR REGRESSION & GRADIENT DESCENT | Machine Learning Practices | Session - 9 

LINEAR REGRESSION & GRADIENT DESCENT | Machine Learning Practices | Session - 9
Please fill this feedback form to rate my sessions:
forms.gle/pMaacwzLzkt366dq8
In this session, we've covered:-
- Linear Regression (Explanation)
- Linear Regression Implementation from Scratch
- Cost Function - Mean Squared Error
- Gradient Descent
- Regularization: Ridge, Lasso
Kaggle notebook 🔼 (Make sure to upvote it):
www.kaggle.com/param302/mlp-s...
Want to attend my Live Sessions?
I usually take them twice a week - Wednesday & Sunday, at 6 pm.
You can join my session calendar for details and meet links:
calendar.google.com/calendar/...
Chapters:
00:00 Intro
02:50 ML Algorithms & Techniques
06:44 Intuition - Linear Regression
15:55 Formula - Linear Regression
17:29 Notations - Linear Regression
20:13 How Slope works
21:21 How Intercept works
25:33 Interactive Visualization for W & B
27:45 Mean Squared Error - Cost Function
40:24 Interactive Visualizations for MSE/MAE
43:33 Gradient Descent Intuition
56:10 Gradient Descent Algorithm
58:00 3D Visualization of Cost Function
01:48:31 Linear Regression Implementation
01:11:11 Cost Function MSE Implementation
01:16:42 Learning Rate α
01:22:23 Gradients Implementation
01:31:10 Epochs/Iterations/Steps
01:31:46 Gradient Descent Implementation
01:41:25 Running Gradient Descent
01:43:30 Plotting Regression line
01:49:40 Tweaking Epochs & Alpha
01:57:00 Regularization
01:57:16 (L1) Lasso Regularization
01:59:13 (L2) Ridge Regularization
02:00:40 Linear Regression variants in Scikit-learn
Follow me on my social handles:
Bio link 🔗 param302.bio.link
Twitter 🔗 / param3021
LinkedIn 🔗 / param302
Github 🔗 github.com/Param302
Kaggle 🔗 kaggle.com/param302

Наука