Three reasons why I recommend the MOOCs of Machine Learing in Coursera

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There is no doubt that machine learning is a hot topic in 2014.  It is difficult, however, to answer what machine learning is.  I think the best way to understand machine learning is taking MOOCs by Andrew Ng in Stanford university at Coursera.  Actually, I am taking this course now and I am able to understand how to program complex mechanism in machine learning. This is amazing as it is free and available to everyone.  I would like to present three reasons why I recommend this course to everyone.

 

1.  Several models are explained and compared each other in the course

In this course, we can learn regression models, support vector machines, neural networks, unsupervised learning algorithms.  In addition, we can compare them each other.  So it is good to obtain an overview of machine learning.  Of course we can implement algorithm of each method by using MATLAB/Octave. You can be an expert of machine learning after completion of this course.

 

2.  The math theories behind the algorithms are also explained in it.

When each algorithm is introduced,  math theory behind them are also explained.  Even thought it is high level,  rather than proof of them,  it is useful because  it can help us to understand what the theory behind the algorithms is and we do not need to treat machine learning as “black box”.  I do not think math at postgraduate level is needed in this course.  If you are not familiar with math, there is no need to worry as basic linear algebra lecture is available in the course. This linear algebra lecture starts with high school level and covers everything which is needed in the course. I like it very much!

 

3.  Best practice in the industry is also presented

Dr.Andew Ng, who is the instructor of this course, has been working in the IT industries and currently works for Baidu as their Chief Scientist . So he provides us a lot of best practice in analyzing data by machine learning. It is very important because I assume that most participants in this course are practitioners rather than theorists.  I hope a lot of  startups will be born based on the best practice presented in this course.

 

These three points above keep a good balance in the course. Therefore, even beginners of machine Learning can understand how it works in theory and practice. I cannot say it is easy to pass the program exercises in this course if you are not familiar with MATLAB/Octave, however, I can say it is worth just looking at the video lectures of this course. Although it takes 10 weeks to complete,  you can learn anytime and anywhere through internet once you register the course. I want to give a strong recommendation to this course  for your career development. It might be also good for high school students who is interested in programming. I would like to appreciate Dr. Andew Ng, who prepares this great course.  This is a treasure for everyone!

 

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One thought on “Three reasons why I recommend the MOOCs of Machine Learing in Coursera

  1. Pingback: I think it is good to learn how models work on recommender systems! | toshistats

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