Machine Learning with Python IBM Full Course | Python Machine Learning Basic | Scikit Learn
Machine Learning with Python A Practical Introduction IBM Full Course, Python Machine Learning Basics, Basic Machine Learning for Data Science, Scikit Learn
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Course Contents
00:00:00 Course Introduction
00:02:46 An Overview of Machine Learning
00:10:46 Machine Learning Model Lifecycle
00:12:48 A Day in the life of a Machine Learning Engineer
00:20:28 Data Scientist vs AI Engineer
00:30:58 Tools for Machine Learning
00:39:32 Scikit-learn Machine Learning Ecosystem
00:44:36 Introduction to Regression
00:48:59 Introduction to Simple Linear Regression
00:54:06 Multiple Linear Regression
01:01:42 Polynomial and Non-Linear Regression
01:08:55 Introduction to Logistic Regression
01:15:28 Training a Logistic Regression Model
01:21:53 Classification
01:27:34 Decision Trees
01:34:38 Regression Trees
01:40:42 Supervised Learning with SVMs
01:47:42 Supervised Learning with KNN
01:54:08 Bias, Variance and Ensemble Models
02:00:35 Clustering Strategies and Real-World Applications
02:07:54 K-means and More on K-means
02:15:21 DBSCAN and HDBSCAN
02:21:57 Clustering Dimension Reduction & Feature Engineering
02:26:37 Dimension Reduction Algorithms
02:31:19 Classification Metrics and Evaluation Techniques
02:37:40 Regression Metrics and Evaluation Techniques
02:43:10 Evaluating Unsupervised Learning Models
02:50:23 Cross Validation an Advanced Model Validation Techniques
02:56:08 Regularization in Regression and Classification
03:03:13 Data Leakage other regression
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