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Welcome to Machine Learning for Beginners, where we break down the most important foundations of ML: Data Preprocessing and Machine Learning Models. In this session, you’ll learn how to transform raw data into meaningful insights and build your first ML models step-by-step. 🔍 What You’ll Learn: ✔ What is Machine Learning and how it works ✔ Why Data Preprocessing is critical before model training ✔ Handling missing values and cleaning datasets ✔ Standardization & Normalization (Feature Scaling) ✔ Encoding categorical variables ✔ Introduction to popular Machine Learning Models ✔ Training and evaluating ML models in Python This tutorial is perfect for students, beginners, and aspiring data scientists who want practical knowledge of Python, data science, and machine learning fundamentals. By the end of this session, you’ll understand the complete Machine Learning pipeline, from dataset preparation to model training and evaluation. Whether your goal is to become a Machine Learning Engineer, Data Scientist, or AI Developer, this is your starting point. 👉 Don’t forget to like, share, and subscribe for more sessions on Deep Learning, AI projects, and advanced ML techniques. . . . . Machine learning for beginners, data preprocessing in machine learning, machine learning models explained, ML pipeline tutorial, Python machine learning tutorial, feature scaling in Python, standardization vs normalization, supervised learning models, classification and regression models, beginner ml course, data cleaning for machine learning, AI and ML tutorial . . . . . #MachineLearning #MachineLearningForBeginners #DataPreprocessing #MLModels #PythonForML #DataScience #AI #LearnMachineLearning #FeatureScaling #Standardization #Normalization #SupervisedLearning #Classification #Regression #MLBootcamp