Machine Learning For Absolute Beginners

  Section 1 : An Introduction to Machine Learning
1
Introduction Preview
2
What is Machine Learning
3
Types and Applications of ML
4
AI vs ML
5
Essential Math for ML and AI

  Section 2 : Supervised Learning - Part 1
6
Introduction to Supervised Learning
7
Linear Methods for Classification Preview
8
Linear Methods for Regression
9
Support Vector Machines
10
Basis Expansions
11
Model Selection Procedures
12
Bonus! Supervised Learning Project in Python Part 1
13
Bonus! Supervised Learning Project in Python Part 2

  Section 3 : Unsupervised Learning
14
Introduction to Unsupervised Learning
15
Association Rules Preview
16
Cluster Analysis
17
Reinforcement Learning
18
Bonus! KMeans Clustering Project

  Section 4 : Neural Networks
19
Introduction to Neural Networks
20
The Perceptron
21
The Backpropagation Algorithm
22
Training Procedures Preview
23
Convolutional Neural Networks

  Section 5 : Real World Machine Learning
24
Introduction to Real World ML
25
Choosing an Algorithm
26
Design and Analysis of ML Experiments
27
Common Software for ML

  Section 6 : Final Project
28
Setting up OpenAI Gym
29
Building and Training the Network Part 1
30
Building and Training the Network Part 2