Machine learning is a rapidly growing field. However, a lot of courses on the internet today do not go over some of it's most powerful algorithms. In this video, we will learn multiple machine learning algorithms, along with data preprocessing, all in under an hour. We will go over regression, classification, component analysis and boosting all in scikit-learn, one of the most popular machine learning libraries for python. Code for this video: https://github.com/KhanradCoder/LearnMachineLearning Want to learn more machine learning? Check out my deep learning course with keras: https://www.youtube.com/watch?v=5VTE8IZgIco Or explore some resources that I've put together here: https://github.com/KhanradCoder/LearnMachineLearning 0:00 Introduction 2:00 Data preprocessing Regression: 9:17 Simple Linear Regression 16:35 Polynomial Regression 20:16 Multiple Linear Regression Classification: 31:20 Logistic Regression 43:31 Support Vector Machines (SVM) 46:12 Decision Trees 49:05 Random Forest Optimization: 53:09 PCA 1:01:01 Gradient Boosting 1:03:28 XGBoost Get 60 Free Days of Unlimited Access to Scribd! https://www.scribd.com/g/6lchwh Follow Me: Twitter: https://twitter.com/khanradcoder Instagram: https://instagram.com/thekhanradcoder/ GitHub: https://github.com/KhanradCoder