Machine Learning with Scikit-Learn

Dive into a comprehensive 30-minute video tutorial on machine learning using Scikit-Learn and Python. Explore hands-on techniques for working with datasets, implementing various algorithms such as K-Nearest Neighbors, Logistic Regression, Decision Trees, and Neural Networks. Learn essential preprocessing steps including scaling, normalization, and one-hot encoding. Discover methods for automatic feature selection to optimize your models. Gain practical insights into applying these powerful tools for real-world machine learning tasks.

Syllabus

Hands-On Machine Learning with Scikit-Learn and Python - Course Preview.
Machine Learning with Scikit-Learn - The Dataset - 1.
Machine Learning with Scikit-Learn - Part 2.
Machine Learning with Scikit-Learn - Part 3.
Machine Learning with Scikit-Learn - Part 5 - KNN 1.
Machine Learning with Scikit-Learn - Part 8 - Logistic Regression 1.
Machine Learning with Scikit-Learn - Part 11 - Decision Trees 1.
Machine Learning with Scikit-Learn - Part 19 - Neural Networks 1.
Machine Learning with Scikit-Learn - Part 37 - Preprocessing - Scaling.
Machine Learning with Scikit-Learn - Part 38 - Preprocessing - Normalization.
Machine Learning with Scikit-Learn - Part 40 - One Hot Encoding 1.
Machine Learning with Scikit-Learn - Part 42 - Automatic Feature Selection 1.