As a guy that tries to live his professional life in the middle of the dichotomy “C/C++ - JavaScript”, I often find myself discussing the discrepancies, differences and implementation details of the latter (an half-assed prototypal language) using the former. The other day I was chatting with Luca (@lucabox) about scope in JS, and we were describing the different situations you can end up with… and how we work our way out of those culprits. ...
In 2006 I decide that I wanted to leave my home country. I wanted to try hard and make some space for me in the world (well, the tech-world). I was really tired of being paid fuck all, dealing with a country driven by old-and-hard-to-die politicians, not seeing any foreseeable future in front of me. I made a decision, and I started working towards my leaving (I finishing uni, so this required a bit of planning). ...
I have been thinking about what to write in this post since the day I took the final exam of the Stanford Online AI Class. I have so many things to say (and still to do), that I have a mess of mixed thoughts in my head. So, I apologise in advance if thoughts will sound a bit random. Amazing experience That’s what this class has been for me. I have learnt tons of new things, all thanks to the great work of prof. Thrun and Norvig. I digged into the amazing topic of Artificial Intelligence, and now I feel a bit more “round” as a Computer Scientist. ...
I borrowed the title from a guy who kickstarted all of this. Thanks Ariya ;) I’m leaving Betfair. I owe a lot to this company: for a bit longer than a year I have had the pleasure to work with smart, enlightened, knowledgeable people from which I learned loads. Leaving was definitely not an easy choice. The only thing didn’t happen, is that I didn’t become a proper punter: I just learned that even something sounding “boring” as betting on sports, can actually be a very big challenge in terms of the technologies involved. Even more, if you try to do it in the Betfair way: with million of customers, all constantly hammering the servers to make the most out of their money. ...
I decide that is very little point in keep writing posts just to highlight new notes, as I finish to write them. So, I decide to just share with the world all my notes about the ai-class. You will find them in (sort of) chronological order, and will give also an idea on how I studied so far (as every material I produced is in there). About the homework, I’ll make sure NOT TO PUBLISH THEM BEFORE the respective deadline: I don’t want to break the Stanford Honor Code. ...
I have been very busy at home and in the weekend, so I’m a bit behind with study and sharing my notes. I just finished going through the very interesting lesson 9, and I now have to start with lesson 10. I plan to do it on Saturday: tomorrow is a special night! ;-) Instead, regarding lesson 8, I just managed to put down the list of topics discussed, but for lack of time I didn’t put anything in writing just yet. Will eventually do it (maybe). ...
Recently, I’m donating my spare time to the amazing Stanford Online AI Class, and writing down notes takes time. But I’m still working, in the spare time of the spare time, on PhantomJS. Yes, very slowly, but I’m not stall. Recently two ideas have come to mind, and it’s stuff I’d love to see supported by PhantomJS. REPL From the Wikipedia article: A read–eval–print loop (REPL), also known as an interactive toplevel, is a simple, interactive computer programming environment. […] In a REPL, the user may enter expressions, which are then evaluated, and the results displayed. ...
If the “mood” of the previous lessons was about Inference, I can only say that the current are about “smoothing”, “occam’s razor” and “perceptron”. 3 concepts that will remain with you even after having forgotten about all this (check it out below :-P). My notes of Lesson 5 My notes of Lesson 6 Enjoy the notes and, again, do Lesson 5, than complete the Homework, than study Lesson 6. UPDATE Sat 05 Nov 2011: I just finished putting down the notes of Lesson 6, and you can find the link above. ...
This week the ai-class was about Probability, Bayes Networks and Inference. For people like me, that have to find patches of free time to study this course, there is a good news: you can do Homeworks 2 just by studying the first of the 2 lessons. This can help to prioritise your schedule, and study the second lesson (that focuses on the “computation” over Bayes Networks) with a little bit more peace of mind. ...
Recently the online class “Introduction to Artificial Intelligente” has began. Prof. Sebastian Thrun and Prof. Peter Norvig, from Stanford University, are offering it for free. And I’m enjoying every minute of it. The idea is to trasport to the web the same course that they are teaching in person at Stanford. Almost simultaneously. One of the great notes from larvecode. It’s in my opinion a great experiment: there are 160,000 students, and will be interesting to see how it pans out. The two profs are doing their best to “leverage the scalability of the web”, instead of trying to retrofit the web into the class. That is smart. And gives them more chances of success. ...