Any courses similar to Berkeley’s CS61A but with Python? Computer Science |
- Any courses similar to Berkeley’s CS61A but with Python?
- Facebook Open-Sources PySlowFast Codebase for Video Understanding
- Real world work of a Cs student?
- Crawling algorithm that doesn't end in a massive messy chain reaction?
| Any courses similar to Berkeley’s CS61A but with Python? Posted: 10 Jan 2020 09:26 PM PST |
| Facebook Open-Sources PySlowFast Codebase for Video Understanding Posted: 10 Jan 2020 08:36 AM PST |
| Real world work of a Cs student? Posted: 10 Jan 2020 09:31 AM PST Sorry for the cliche question and title. I'm doing Cs undergrad right now. I'm not interested much towards application development and Web development but when i try to think what people might do in the real working field all it crosses my mind is that we should probably join some sort of app development field in some way. I don't know what I'm missing.. Please explain what is irl work other than working for apps or softwares? Like maybe I'm interested in competitive coding or maybe AI or ml etc.. What are the opportunities available? Sorry if question is vague [link] [comments]  |
| Crawling algorithm that doesn't end in a massive messy chain reaction? Posted: 10 Jan 2020 03:53 PM PST I am currently trying to rewrite a crawler of a p2p network to make more sense (it is currently badly designed but works). Essentially with this network I can call one node and get 20 or so of its "closest peers" - this is pretty much how I discover new nodes. The speed of this algorithm isn't really important, however I don't want it to be inefficient obviously. At the moment, my program starts with a list of about 100 nodes. It adds each one to the database, and then finds the 20 "closest peers" of each one of the nodes in the database, and then adds all of these new nodes to the database too. My program will then go back to the database and pick another 100 randomly (although it'll go for ones that haven't had their "closest peers" imported first) selected nodes, and then repeat. I don't know if this is necessarily a bad design but it does seem a bit dumb to me. I want to rewrite this to use a breadth-first approach for crawling the network - and from what I have read online, it seems to be the preferred approach for web crawling. But what I don't get is: how doesn't it just become a massive slow chain reaction. Like within a few layers of the tree (like a graph of the network), it'll get so slow and not explore the network fully. At least with my current application there is some randomness so it adds a lot of variety in exploring the network, unlike the breadth-first approach. So my question I guess is, is there a better way of doing this? In my head it seems like the breadth-first approach wouldn't find more nodes, so why is it used? IDK this post may come off as very confusing but I am quite confused. [link] [comments]  |
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