📚Data ScienceEN
Introduction to Machine Learning
A comprehensive introduction to machine learning covering supervised and unsupervised learning, key algorithms (linear regression, decision trees, SVMs, neural networks), model evaluation, feature engineering, and the end-to-end ML workflow with Python and Scikit-Learn.
10 lessons
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Lessons
What is Machine LearningPreview
Supervised Learning
Unsupervised Learning
Linear and Logistic Regression
Decision Trees and Random Forests
Support Vector Machines
Introduction to Neural Networks
Model Evaluation and Validation
Feature Engineering and Preprocessing
Machine Learning Workflow and Best Practices