📊 Linear Regression in 2026 | AI ML Explained 🚀 #machinelearning #datascience #ai

In this 10‑minute educational video, Dhaarini AI-Tech Research Academy explains why Linear Regression remains a cornerstone of Machine Learning in 2026. 🌐 🔹 2026 Context: While deep learning often creates "black box" models, industries now prioritize speed, interpretability, and lightweight solutions that run on CPUs for digital sovereignty. 🔹 Core Concepts: Learn how Linear Regression models the relationship between independent variables (X) and a dependent target (Y), finding the "line of best fit." 🔹 Mathematical Blueprint: Step‑by‑step explanation of the cost function (SSE), Ordinary Least Squares (OLS), and Gradient Descent for big data environments. 🔹 Scikit‑learn Demo: Hands‑on Python implementation using scikit‑learn and pandas, with the diabetes dataset to predict disease progression scores. 🔹 Evaluation: Understand R² (coefficient of determination), Mean Squared Error (MSE), and the importance of monitoring data drift with retraining pipelines. 🎯 Outcome: By the end of this video, students, researchers, and professionals will gain practical knowledge of regression techniques and their strategic role in building sustainable AI solutions. 👉 Subscribe to Dhaarini AI-Tech Research Academy for more AI/ML tutorials, projects, and research insights in English! 🔑 SEO Keywords + Hashtags Linear Regression tutorial, Machine Learning 2026, AI education, Regression analysis, Python ML, Scikit-learn demo, Data Science projects, AI training English, ML explained, AI future #AI #MachineLearning #DataScience #LinearRegression #Python #ScikitLearn #MLProjects #AITraining #DhaariniAcademy #education