Scikit-Learn Full Crash Course - Python Machine Learning

Today we to a crash course on Scikit-Learn, the go-to library in Python when it comes to traditional machine learning algorithms (i.e., not deep learning). Scikit-Learn Docs: https://scikit-learn.org/stable/api/index.html ◾◾◾◾◾◾◾◾◾◾◾◾◾◾◾◾◾ 📚 Programming Books & Merch 📚 🐍 The Python Bible Book: https://www.neuralnine.com/books/ 💻 The Algorithm Bible Book: https://www.neuralnine.com/books/ 👕 Programming Merch: https://www.neuralnine.com/shop 💼 Services 💼 💻 Freelancing & Tutoring: https://www.neuralnine.com/services 🖥️ Setup & Gear 🖥️: https://neuralnine.com/extras/ 🌐 Social Media & Contact 🌐 📱 Website: https://www.neuralnine.com/ 📷 Instagram: https://www.instagram.com/neuralnine 🐦 Twitter: https://twitter.com/neuralnine 🤵 LinkedIn: https://www.linkedin.com/company/neuralnine/ 📁 GitHub: https://github.com/NeuralNine 🎙 Discord: https://discord.gg/JU4xr8U3dm Timestamps: (0:00) Intro (1:49) Environment Setup (5:32) Preview Example (12:22) Datasets (23:12) Splitting Data (33:02) Preprocessing (41:35) Feature Encoding (52:51) Classification (1:00:27) Regression (1:04:48) Clustering (1:12:58) PCA (1:18:04) Metrics (1:23:33) Cross-Validation (1:25:37) Hyperparameter Tuning (1:31:04) Pipelines (1:32:53) Outro