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TIMESTAMPS

00:00 - Introduction
1:49 Machine learning, what happens behind the scenes, and basic concepts
2:57 Machine learning types
3:11 Supervised learning
4:40 Linear Regression and Fundamental Assumptions
5:29 Understanding Linear Regression
6:53 Linear Regression – Line of best Fit
7:54 Understanding Characteristics of a Line - Slope, Intercept
8:29 Data and Line of best fit
9:56 Training of Algorithm
11:11 Objective Function Costs
13:29 Learning Algorithm – Gradient Descent
14:41 What happens when you change w and b
15:16 Machine Learning – Fundamental steps and recap
16:09 Gradient Descent
16:41 Machine Learning in a Nutshell
17:03 Demo
37:01 Audience Q&A and Programme Overview