Quantitative thoughts

For those who did not know, Stanford university offered free off charge 3 courses at beginning of the autumn. It is kind of shocking – US based institution offers education for free! Take any socialism oriented country and one of the promises is education for free. But it seems, that the argument loosing the power – Stanford, khanacademy and bunch of others offer high quality learning for everyone.

In January (scroll down to get full list), Stanford will provide more than 15 courses for free and I thought that I could provide my based opinion about the courses.

ml-class.com This course was perfect fit for my personality and I loved it. Every week there was video lessons about the topics like machine learning, datamining, and statistical pattern recognition, overview questions and programming exercises, which had to be completed in Octave/Matlab. The quality of the video was superb, the length of the lessons was 8-14 minutes and format of the lessons was great as well (Prof. Andrew Ng was seamlessly switching between the white board and talks).
This course inspired me to build anomaly detection system at my work, where we already spotted few anomalies. Now I’m working on  kind of “spam filter implementation” for text analysis.
For me, the practical part of the course is like the water for the fish – without it theoretical part is empty and to be forgotten within the hours.

ai-class.com This course gave to me a broad view about artificial intelligence: machine learning, robotics, natural language processing, computer vision, search algorithms and etc. I suppose, that because the topics are so different the course was align towards theoretical part – otherwise the practical parts would take forever. However, in the last part there was an optional exercise – to encrypt two texts, which I loved!
The instructors, namely Sebastian Thrun and Peter Norvig, recommend this book: Artificial Intelligence: A Modern Approach. I should say, that the book was very helpful during the course and but I won’t use it outside the course.
The courses have different evaluation systems. AI class will score your homework and exams, where the top 1% will be awarded with special paper and maybe a job offer, while ML class inclined towards delivering knowledge – almost everyone working hard could get 100% score without a penalty. I think, that based on such environments, different communities sprang up - aiqus.com forum is very harsh to any question, where the answers start by stating, like “I know the answer, but hey, I can’t tell you anything, because honor code doesn’t allow and I’m the smartest guy on the Earth”, while ml-class forum is more open minded – if you can’t crack the problem then other students will help you.
I was in light shock, when I saw the format of AI lectures first time – the instructors used real white board, namely paper and pencil and took me a while to get use it.

But overall, I really really enjoy both courses and special thanks to Stanford professors, concretely Andrew Ng, Sebastian Thrun and Peter Norvig!

During the summer I was contacted by a hedge fund from Bahamas. The fund was looking for someone with R language skills on-site and insisted for phone interview. Besides obvious questions about finance, statistics, coding and how many tennis balls can fit in Boeing 747 (ok, this question was omitted), they wanted to know if I code in C++. So, I told them true – the last time I wrote a line in C++ was more or less 10 years ago. Long story short – it made me thinking about existence of C++.

10 yeas ago I was told, that C++ is going to disappear soon and Java is the king. At that time neither HN nor stackoverflow existed (meaning, that I had to rely on limited source), so I took it for granted, so here I am.

What do we have 10 years later? Neither C++ is dead, nor Java is sexy anymore. Actually is opposite – if you use Java, then you are clumsy programmer with lack of imagination. Does it sounds offensive? Then read for example the comments of Scala vs Java article and you will get the same feeling. Replacement of  Sun with Oracle does not help either.

But lets go back to C++. Google trends says, that C++ enjoys either maturity or decline. However, if you concentrate on specific industry, you will have a different picture. Kernel development (C not C++), game industry, number crunching, data mining, finance – where C++ matters. I know, I know, that you can write a magic code with Ruby or Python and it will perform almost as C++. And I saw a video, where guys were claiming, that they tuned “a bit”  Java and now it is able to deal with more that 1 million requests a second. Only the thing they did was elimination of garbage collection. The question – is it really worth of doing that way?

Next thing is to check what is demand for C++. Time to time I scroll through HN to be millionaires list and strangely enough C++ is demanded for back end systems, where performance or data amount is an issue. However, if you are targeting finance industry exclusively, then you may find this discussion interesting. Basically, it says, that there is stable demand for C++. Worth to say nonetheless, that C++ is mostly used by front and middle offices (where quants live) and the demand diminish in back office.

With such subjective study in mind I purchased C++ Primer by Stanley B. Lippman, which I recommend to beginners or disillusioned users like me. So far I built 2 small projects and in which one of them I parse 1.5 million terms to get a list of most used terms. R language does that in minutes, C++ in seconds.

Welcome back C++. It seems, that I miss you.