Syllabus – What you will learn from this course
1.Introduction
2.Linear Regression with One Variable
3.Linear Algebra Review
4.Linear Regression with Multiple Variables
5.Octave/Matlab Tutorial
6.Logistic Regression
7.Regularization
8.Neural Networks: Representation
9.Neural Networks: Learning
10.Advice for Applying Machine Learning
11.Machine Learning System Design
12.Support Vector Machines
13.Unsupervised Learning
14.Dimensionality Reduction
15.Anomaly Detection
16.Recommender Systems
17.Large Scale Machine Learning
18.Application Example: Photo OCR
Skills you will gain
Logistic Regression
Artificial Neural Network
Machine Learning (ML) Algorithms
Machine Learning
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