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1 ืฆืคื™ื•ืชยท 16 ืื•ื’ื•ืกื˜ 2022

Machine Learning Course for Beginners

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MaggieN383
ืžื ื•ื™ื™ื

Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.

๐Ÿ”— Course website with learning resources: https://antern.co/pages/ml001.html
๐Ÿ’ป Code: https://github.com/ayush714/ML....001-Project-Sources-

โœ๏ธ Course developed by Ayush Singh. Check out his channel: https://www.youtube.com/c/neweraa

โญ๏ธ Course Contents โญ๏ธ
โŒจ๏ธ (0:00:00) Course Introduction
โŒจ๏ธ (0:04:34) Fundamentals of Machine Learning
โŒจ๏ธ (0:25:22) Supervised Learning and Unsupervised Learning In Depth
โŒจ๏ธ (0:35:39) Linear Regression
โŒจ๏ธ (1:07:06) Logistic Regression
โŒจ๏ธ (1:24:12) Project: House Price Predictor
โŒจ๏ธ (1:45:16) Regularization
โŒจ๏ธ (2:01:12) Support Vector Machines
โŒจ๏ธ (2:29:55) Project: Stock Price Predictor
โŒจ๏ธ (3:05:55) Principal Component Analysis
โŒจ๏ธ (3:29:14) Learning Theory
โŒจ๏ธ (3:47:38) Decision Trees
โŒจ๏ธ (4:58:19) Ensemble Learning
โŒจ๏ธ (5:53:28) Boosting, pt 1
โŒจ๏ธ (6:11:16) Boosting, pt 2
โŒจ๏ธ (6:44:10) Stacking Ensemble Learning
โŒจ๏ธ (7:09:52) Unsupervised Learning, pt 1
โŒจ๏ธ (7:26:58) Unsupervised Learning, pt 2
โŒจ๏ธ (7:55:16) K-Means
โŒจ๏ธ (8:20:21) Hierarchical Clustering
โŒจ๏ธ (8:50:28) Project: Heart Failure Prediction
โŒจ๏ธ (9:33:29) Project: Spam/Ham Detector

๐ŸŽ‰ Thanks to our Champion and Sponsor supporters:
๐Ÿ‘พ Wong Voon jinq
๐Ÿ‘พ hexploitation
๐Ÿ‘พ Katia Moran
๐Ÿ‘พ BlckPhantom
๐Ÿ‘พ Nick Raker
๐Ÿ‘พ Otis Morgan
๐Ÿ‘พ DeezMaster
๐Ÿ‘พ AppWrite

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