Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
Learning resources:
Code:
️ Course developed by Ayush Singh. Check out his channel:
️ Course Contents ️
⌨️ (0:00:00) Course Introduction
⌨️ (0:04:34) Fundamentals of Machine Learning
⌨️ (0:25:22) Supervised Learning and Unsupervised Learning In Depth
⌨️ (0:35:39) Linear Regression
⌨️ (1:07:06) Logistic Regression
⌨️ (1:24:12) Project: House Price Predictor
⌨️ (1:45:16) Regularization
⌨️ (2:01:12) Support Vector Machines
⌨️ (2:29:55) Project: Stock Price Predictor
⌨️ (3:05:55) Principal Component Analysis
⌨️ (3:29:14) Learning Theory
⌨️ (3:47:38) Decision Trees
⌨️ (4:58:19) Ensemble Learning
⌨️ (5:53:28) Boosting, pt 1
⌨️ (6:11:16) Boosting, pt 2
⌨️ (6:44:10) Stacking Ensemble Learning
⌨️ (7:09:52) Unsupervised Learning, pt 1
⌨️ (7:26:58) Unsupervised Learning, pt 2
⌨️ (7:55:16) K-Means
⌨️ (8:20:21) Hierarchical Clustering
⌨️ (8:50:28) Project: Heart Failure Prediction
⌨️ (9:33:29) Project: Spam/Ham Detector
Thanks to our Champion and Sponsor supporters:
Wong Voon jinq
hexploitation
Katia Moran
BlckPhantom
Nick Raker
Otis Morgan
DeezMaster
AppWrite
--
Learn to code for free and get a developer job:
Read hundreds of articles on programming: