Machine Learning Course for Beginners
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
๐ Learning resources: https://github.com/ayush714/ML001-Project-Sources-Code-and-Learning-Materials
๐ป Code: https://github.com/ayush714/ML001-Project-Sources-Code-and-Learning-Materials
โ๏ธ Course developed by Ayush Singh. Check out his channel: https://www.youtube.com/c/neweraa
โค๏ธ Try interactive AI courses we love, right in your browser: https://scrimba.com/freeCodeCamp-AI (Made possible by a grant from our friends at Scrimba)
โญ๏ธ Course Contents โญ๏ธ
โจ๏ธ (0:00:00) Course Introduction
โจ๏ธ (0:04:34) Fundamentals of Machine Learning
โจ๏ธ (0:25:22) Supervised Learning and Unsupervised Learning In Depth
โจ๏ธ (0:35:39) Linear Regression
โจ๏ธ (1:07:06) Logistic Regression
โจ๏ธ (1:24:12) Project: House Price Predictor
โจ๏ธ (1:45:16) Regularization
โจ๏ธ (2:01:12) Support Vector Machines
โจ๏ธ (2:29:55) Project: Stock Price Predictor
โจ๏ธ (3:05:55) Principal Component Analysis
โจ๏ธ (3:29:14) Learning Theory
โจ๏ธ (3:47:38) Decision Trees
โจ๏ธ (4:58:19) Ensemble Learning
โจ๏ธ (5:53:28) Boosting, pt 1
โจ๏ธ (6:11:16) Boosting, pt 2
โจ๏ธ (6:44:10) Stacking Ensemble Learning
โจ๏ธ (7:09:52) Unsupervised Learning, pt 1
โจ๏ธ (7:26:58) Unsupervised Learning, pt 2
โจ๏ธ (7:55:16) K-Means
โจ๏ธ (8:20:21) Hierarchical Clustering
โจ๏ธ (8:50:28) Project: Heart Failure Prediction
โจ๏ธ (9:33:29) Project: Spam/Ham Detector
๐ Thanks to our Champion and Sponsor supporters:
๐พ Wong Voon jinq
๐พ hexploitation
๐พ Katia Moran
๐พ BlckPhantom
๐พ Nick Raker
๐พ Otis Morgan
๐พ DeezMaster
๐พ AppWrite
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