Machine Learning for Beginners

A comprehensive introductory course to machine learning, covering fundamental concepts, algorithms, and practical applications using Python.

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Introduction to Machine Learning

Unit 1: Understanding Machine Learning Fundamentals

Unit 2: The Machine Learning Workflow

Data Preprocessing and Feature Engineering

Unit 1: Handling Missing Data

Unit 2: Data Scaling and Normalization

Unit 3: Encoding Categorical Features

Unit 4: Feature Engineering Techniques

Unit 5: Data Splitting

Supervised Learning Algorithms

Unit 1: Linear Regression Fundamentals

Unit 2: Logistic Regression for Classification

Unsupervised Learning and Dimensionality Reduction

Unit 1: K-Means Clustering

Unit 2: Hierarchical Clustering

Unit 3: Principal Component Analysis (PCA)

Model Evaluation, Deployment, and Trends

Unit 1: Model Evaluation Metrics

Unit 2: Cross-Validation Techniques