Supervised Learning Algorithms Explained | Ridge, SGD, LDA & Quantile Regression

Learn Supervised Machine Learning Algorithms with real code and intuitive explanations!

In this video, we explore four essential supervised learning techniques — Ridge Regression, Quantile Regression, Stochastic Gradient Descent (SGD), and Linear Discriminant Analysis (LDA) — with hands-on examples using Jupyter notebooks.

You’ll learn:
✔ What these algorithms are
✔ How they work intuitively
✔ When to use each of them
✔ Python implementation and results

📂 Resources & Code Files (GitHub)
🔗 Presentation PPT: https://github.com/krthiksha/Machine-Learning-Classification_module/blob/main/OTHER%20SUPERVISED%20ALGORITHMS/supervised%20learning%20algorithm%20-%20ridge%2C%20SGD%2C%20LDA%2C%20quantile.pdf

🔗 Ridge Regression Notebook: https://github.com/krthiksha/Machine-Learning-Classification_module/blob/main/OTHER%20SUPERVISED%20ALGORITHMS/Ridge_regression.ipynb

🔗 Quantile Regression Notebook: https://github.com/krthiksha/Machine-Learning-Classification_module/blob/main/OTHER%20SUPERVISED%20ALGORITHMS/QuantileRegressor.ipynb

🔗 SGD Notebook: https://github.com/krthiksha/Machine-Learning-Classification_module/blob/main/OTHER%20SUPERVISED%20ALGORITHMS/Stochastic%20Gradient%20Descent.ipynb

🔗 LDA Notebook: https://github.com/krthiksha/Machine-Learning-Classification_module/blob/main/OTHER%20SUPERVISED%20ALGORITHMS/Linear%20Discriminant%20Analysis.ipynb
#machinelearning #supervisedlearning #RidgeRegression #Quantile Regression #SGD #stochastic #gradientdescent #LDA #linear #ai #python #ml #Scikit-Learn #datascience #Algorithms #python #jupyternotebook

Видео Supervised Learning Algorithms Explained | Ridge, SGD, LDA & Quantile Regression канала G.krithiksha