Скачать или смотреть Regression Analysis Explained: Simple & Multiple Regression for Machine Learning

Notes:

https://drive.google.com/file/d/1rjXq...

Welcome to Neural Notes!

In this foundational Machine Learning video, we master Regression Analysis, the essential Supervised Learning technique used to predict continuous numerical values like house prices, temperature, or sales figures. This algorithm is the cornerstone of predictive modeling in Data Science.

We break down the core mathematics, from the simple $Y = mX + C$ formula to the advanced Least Squares Method, explaining how your model finds the "Best Fit Line" and how to evaluate its accuracy using metrics like R-Squared and MSE.

📘 Topics Covered in This Video (Regression Analysis & Predictive Modeling)
✔ Predicting Numbers: What is Regression?

Definition: The goal of finding a relationship between input variables (X) and a continuous output variable (Y).

Linear vs. Non-Linear: The different shapes data can take.

✔ Simple Linear Regression Explained

The Formula: Understanding the slope ($m$) and intercept ($C$).

The Best Fit Line: The visual representation of the model's prediction.

✔ Core Math: The Least Squares Method

Residuals: The error or distance between the predicted line and the actual data points.

Cost Function: How the model minimizes the sum of squared residuals (MSE) to draw the most accurate line.

✔ Evaluating Performance (Regression Metrics)

R-Squared: How well your model fits the data (The most popular metric).

MSE (Mean Squared Error) & RMSE: The common metrics for measuring the magnitude of prediction errors.

✔ Multiple Regression

Expanding the concept: Predict an output (Y) using several input features (X1, X2, X3...).

🎓 Why This Video Is Useful for You (ML & Statistics)

This video is specially made for:

ML Engineers & Data Scientists

CS/IT Students

Interview Preparation

You will get:
✔ Clear, visual explanations of the Best Fit Line.
✔ Simple breakdown of the Least Squares cost function.
✔ Understanding of the difference between prediction and classification.

📚 Perfect For

Supervised Machine Learning Algorithms

Statistics & Econometrics Fundamentals

Predictive Modeling in Data Science

Regression Exam and Interview Questions

🔔 About Neural Notes

Neural Notes is a channel dedicated to making Computer Science simple. We bring complete subject explanations, exam answers, diagrams, and project ideas in the most understandable format.

📧 Contact: [email protected]

Disclaimer: This video is for educational purposes. NotebookLM is a trademark of Google LLC.

#regressionanalysis #linearregression #multiplerregression #supervisedlearning #machinelearning #datascience #predictivemodeling #leastsquares #rsquared #mse #rmse #statistics #cse #csengineering #neuralnotes