Introduction to Machine Learning with Python
********* LECTURES **********
001 Welcome to the Course
00:00:00 - 001 Introduction
002 Python Review
00:08:26 - 002 Variable Types
00:19:46 - 003 Lists and Functions
00:32:01 - 004 Implementation
003 Numpy
00:51:21 - 005 Numpy Basics
01:00:29 - 006 Implementation
004 Pandas
01:16:02 - 007 Pandas Basics
01:24:15 - 008 Implementation
005 Seaborn
01:38:56 - 009 Distribution and Matrix Plots
01:52:07 - 010 Categorical Plots, Regression Plots, and GridsStyle
02:02:06 - 011 Implementation
006 Introduction to ML
02:16:43 - 012 Goals and Types of Machine Learning
007 Linear Regression
02:34:59 - 013 Linear Regression Theory
02:45:21 - 014 Ordinary Least Squares (OLS)
02:55:42 - 015 Implementation Part 1
03:22:18 - 016 Implementation Part 2
008 Logistic Regression
03:31:52 - 017 Logistic Regression Theory
03:43:32 - 018 Logistic Regression Metrics and Implementation
009 Decision Trees
03:53:08 - 019 Terminology
03:57:28 - 020 Splitting Algorithms
04:06:44 - 021 Random Forests
04:08:43 - 022 Implementation
010 Neural Networks
04:23:49 - 023 Intro to Neural Networks
04:25:27 - 024 Origins of Neural Networks
04:29:06 - 025 What are neural networks
04:32:40 - 026 Activation Functions
04:37:42 - 027 Gradient Descent
04:45:13 - 028 Backpropagation
04:55:53 - 029 Implementation
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