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Francesco R

Francesco R
Tokyo
Master of Business Administration (M.B.A)

Machine Learning

Written 3 years ago
My rating
Francesco R completed this course.

Introduction to Neuroeconomics: How the Brain Makes Decisions

Written 2 years ago
The topic is really fascinating and its cross-disciplinary approach to decision making really worth exploring: there is a lot to learn from neuroeconomical experiments whether you already have a background in economics or in psychology, and prof Klucharev presents plenty of them.

The structure of the course is very clear and gradual, and the bases of the theory are repeated over the course, so it is really difficult to miss them.

The presentation is clear, even though I think the professor's voice is overall quite flat, despite his clear passion over the subject.

Regarding the difficulty, I did not find the course difficult at all, and was able to complete it in half time during normal working weeks. While part of it could be undoubtably due to the prof's clarity and a rational selection of questions, I think that overall the tests lack depth. I would have preferred some question based on the recommended lectures, maybe limiting them to only those which could be made freely accessible.

Anyway, overall a rather good course on a topic which I would like to see covered more by MOOCs.
My rating
Francesco R completed this course, spending 2 hours a week on it and found the course difficulty to be easy.

Miracles of Human Language: An Introduction to Linguistics

Written 2 years ago
My rating
Francesco R completed this course.

Practical Reinforcement Learning

Written 3 months ago
The course well deserves five, or even six, stars for offering this content. Despite the continue fanfares on media and SNS, RL and deep RL are almost never covered by MOOCs, and this course goes even beyond being a “notable exception”. The problems that have been prepared and the assignments based on OpenAI gym are really challenging and entertaining. “Practical” is really a proper attribute of this course, and this does not subtract to the quality of content, as the lecturers provided plenty of links to state-of-the-art techniques - and many assignments make use of discoveries that are just two-three years old.

Alas, at this time it seems however that the bulk of this course on Coursera is just a port of an already existing one on Github. Which would not be bad per se, if only the assignment environment and the graders worked properly...

You need a lot of commitment in order to make everything work - possibly getting help from the discussion platform - and the best bet is to download everything and work offline. Prepare to install or reinstall a lot of Python modules, especially if you work from Windows.

At the time I am writing this, most images within the Jupyter are also not showing and you need to fetch them from the original Github course.
My rating
Francesco R completed this course, spending 9 hours a week on it and found the course difficulty to be medium.

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