This concise guide provides an overview of core machine learning concepts, designed for quick learning and practical application. Key topics include:

  • Introduction to ML

    • Definition and history of machine learning
    • Types: Supervised, Unsupervised, Reinforcement learning
    • Applications in real-world scenarios 🌍

  • Core Algorithms

    • Linear regression 📈
    • Decision trees 🌳
    • Support Vector Machines (SVM) 📊
    • K-means clustering 🧩

  • Practical Tips

    • Data preprocessing 📁
    • Model evaluation metrics 📈
    • Overfitting and regularization ⚖️

For deeper exploration, check our short courses section.

Supervised_Learning

Expand your knowledge with our interactive tutorials or research papers. 🚀