Scikit-learn for Beginners in Python | Machine Learning Tutorial

Learn Scikit-learn in Python with this beginner-friendly, practical Machine Learning tutorial. In this video, we cover essential Scikit-learn tools and techniques used in Data Analytics, Data Science, and Machine Learning. You'll learn how to preprocess data, encode categorical variables, scale features, select important features, split datasets, build regression and classification models, and evaluate model performance using a confusion matrix. This tutorial is designed for beginners who want to understand how to use Scikit-learn to build Machine Learning models in Python. 📌 *Topics Covered:* 00:00 Introduction 04:33 One-Hot Encoding 16:52 Feature Scaling (Standardization) 28:57 Function Transformer 39:42 Feature Selection 57:55 Train-Test Split 1:11:43 Simple Linear Regression 1:30:08 Multiple Linear Regression 1:44:23 Decision Tree Regression 1:56:17 Logistic Regression (Classification) 2:10:19 Confusion Matrix 🎯 *Who Should Watch This Tutorial?* Python beginners interested in Machine Learning Students learning Data Analytics and Data Science Beginners preparing for Machine Learning projects and interviews Anyone who wants to build ML models using Scikit-learn 💻 *Prerequisites:* Basic knowledge of Python, Pandas, and fundamental Machine Learning concepts is helpful. 📚 *Playlist:* Python for Data Analytics and Data Science Subscribe to *Eklavik* for more tutorials on Python, Data Science, Machine Learning, Deep Learning, and Artificial Intelligence. #ScikitLearn #MachineLearning #Python #DataScience #NexTechX