I could completed the Machine Learning course by Stanford University! Yay!

I started in April, and I could finish it at the end of June. So It took about 3 months.

(Please refer to the entry, which was written in the beginning => Started to study Coursera Machine Learning course by Stanford Univ. )

## Cons

- Unfamiliar programming language “Octave”. But Octave is quite intuitive for calculation.
- A bit hard to submit the programming assignment every week, but this became good training.
- Takes time to get remember linear algebra, matrix, partial differentiation, etc…
- I’m not familiar with mathematical terms in English. (I could study many new words)

## Pros

- I could study whole general machine learning algorithms.
- By submitting the programming assignments, I could understand deeper.
- I could keep my motivation very high to understand the class because I can’t complete the assignments if I don’t understand it.
- The great explanation from the teacher Mr. Andrew Ng.
- The logic is explained with mathematics, and it was great he explained very intuitive.
- Coursera issues the course certificate (it’s not free but only $89 and it worths)
- My certificate => Course Certificate

## What I studied

- Cost Function
- Gradient Descent
- Linear Regression
- Logistic Regression
- Neural Networks
- Backpropagation
- Evaluating a Learning Algorithm
- SVM (Support Vector Machines)
- Unsupervised Learning
- Dimensionality Reduction
- Anomaly Detection, Recommender Systems
- Large Scale Machine Learning
- Application Example: Photo OCR

## Strongly recommended!

It was really great that Mr. Andrew Ng explains very intuitive. I could imagine how the equation works and what the logic is. This is very first time for me to study something online, I found it’s very fun and I like it.

It was very good rhythm to study and submit the assignment on the weekend, I’m thinking to start new course.

Well if you want to study Machine Learning, I recommend this course definitely.