#MLConcepts #MachineLearningInPython #MachineLearningForBeginners Looking for a short primer on Machine Learning concepts? SDS Founder Kirill Eremenko and AI expert Hadelin de Ponteves are back, joining @JonKrohnLearns to review essential ML concepts. From classification errors to logistic regression, feature scaling, the elbow method and more. The popular data science instructors also introduce their latest course: Machine Learning in Python: Level 1. In this episode you will learn: • [00:00:00] Catching up with Kirill and Hadelin • [00:15:27] Kirill and Hadelin's new course • [00:24:16] Supervised vs unsupervised learning • [00:29:15] False positives and false negatives • [00:40:53] Logistic regression • [00:44:32] Holding out a set of test data • [00:50:38] Feature scaling • [00:57:37] The Adjusted R-Squared metric • [01:03:05] The five assumptions of linear regression • [01:09:35] The Elbow Method Additional materials: https://www.superdatascience.com/649 Interested in sponsoring a SuperDataScience Podcast episode? Visit https://www.jonkrohn.com/podcast for sponsorship information.