Linear Regression Explained for Beginners | Complete ML Model in Python (Step-by-Step) part 1

In this video, we learn **Linear Regression from absolute beginner level and build a complete Machine Learning model using Python**. This tutorial explains *every step of the Machine Learning workflow* in simple language, making it perfect for beginners. Topics covered in this video: Machine Learning Workflow Problem Understanding Data Collection Data Understanding Data Cleaning Exploratory Data Analysis (EDA) Feature Selection Train Test Split Overfitting vs Underfitting Linear Regression Model Model Training Model Prediction Model Evaluation (MAE, MSE, RMSE, R² Score) Visualization of Results We also understand important concepts like: • What is a *feature* • What is a *target variable* • Why we use *Train Test Split* • How *Scikit-Learn works* • How the *Linear Regression equation* works By the end of this video you will know how to build a **complete Linear Regression machine learning model step-by-step in Python**. This tutorial is ideal for: • Machine Learning beginners • Data Science students • Python learners entering ML • Anyone preparing for ML interviews Dataset used: Diabetes dataset Tools used: Python Pandas NumPy Matplotlib Seaborn Scikit-Learn If you found this helpful, don't forget to like, share and subscribe for more Machine Learning tutorials.