 He's trying to use. What's your plan for the evening? I'm thinking of doing something with Twitter data. Coming up with some sort of results around it. Alright. Good luck. And here is Kiran. He just woke up from... Yeah, so I discovered the secret to working for 24 and 48 hours is to sleep in between. I'm trying the Uberman thing but that's way too hard. So I'm not very shameless. If there's a mattress I'm going to go sleep for an hour and come back. And that's how I continue working for so long. So what's your plan for the evening? I'm actually not doing a data project. I'm instead doing a ASCII project because we have an event to run which needs a lot of code written. So the cameraman, this dude here has been importing CSV files to sync attendee lists. At least we want to work that out. I was looking at that and thinking, man, this has got to be better. So it turns out do it in has an API. It's in closed beta but you can always write to them for an invite. And I have confidential data to show here. I will not let this be on screen too long because there's data in here that you can't copy. Dude, don't let them anybody copy data from the screen. So anyway, it turns out that you can actually make a call to their API and it will give you the full participant list and then you can go to a sync, completely automatic. Nobody has to do download, upload or it's press button or even run a cronja but you do the sync automatically. Cool. So I'm setting it up for Mr. Sajidia so that he could take a break. That's my project for the night. Cool. That's great. He's up too. I'm just playing around with Twitter. You want stuff on the screen. Trying to see what is the difference between South India and South India. But that's what North India treats about. That's what South India treats about. What's Mumbai, Maharashtra, Bangalore? But the circles doesn't make any sense to me. Yeah, I've got to format it a bit. Yeah, but what's HTTP? So the bulk of the tweets, Geocoded tweets in India, there are links are coming from North India. Okay. There's almost no one sending it from South India. Obviously, Delhi, it's talking about Delhi. Okay. North India is talking a lot more about traffic than South India. I don't know if that's a good or bad. North India is sharing a lot more love than South India. South India has got more coffee. Obviously, yeah. More social and media definitely got more leaks. Social media leaks, a lot more love than North India. North India is good. Not bad, yeah. Someone's talking about jobs. Just a point of it. Yeah, North India is looking for jobs more, has more jobs and is really more looking for jobs. So, yeah. Your name and what's your plan for the evening? I'm Kamal. So, what I'm working on is basically on the FDA data that the US FDA supplied. Basically, the data contains information on drugs, demographics and effects on the demographics. So, I've done some basic analysis. So currently, what I'm trying to figure out is the number of girls between the age 30 and 40 and weight 50 and 100 who died. A lot of punchmen, some drug. Some interesting data coming out of it. So, the cost of a benefit will actually kill four girls. So, basically working on... So, some interesting patterns are coming out. Cool. So, can you tell us a bit more about the tools that you're using? Okay. So, one good thing was all the data sizes are almost around, say, one GB. So, what I actually did was I segmented a section of data because I wanted to get some quick results out of it. Okay. So, the cool thing is that it was importable in SQLite. Okay. So, that helped us to sort of get started in learning very quickly. So, almost three hours into the hack, we almost have something like almost five to six concrete results. Like, we know what is happening in what country. Okay. How many people are dying, getting hospitalized and stuff like that. Cool. So, basically, now, after all we have is to get into more details like per country, per gender, per weight. Write down SQL templates for it and then write it down on the script. Generate data and put it out. Cool. Great. Your name and what are you doing for the evening? Hi, Harsh. I'm working on the data set. Okay. You're working along with some... Working along with Kamal. Great. So, using SQLite, just figure out something very interesting. Yeah. We are... If you see, this query would actually show that, you know, when did the event occur and when was it reported to FDR. Okay. Coincidentally, I've taken that if it was reported within 100 days. It's a decent period of time. Yeah, yeah. And, you know, something very interesting. So, the United States is reporting is very bad. And if you see India, it's pretty good. Hmm. That's interesting. It's pretty good. Even the percentage wise, we are reporting it faster than the United States. Cool. Great. Cool. So, your name and what you're doing for this evening? Hi, this is Uttam. I work as an artist for a startup called R2 at Hack Night. I'm trying to visualize school marks of like 10th and 12th students. I'm trying to visualize in the form of clusters, like how the schools are positioned. Geographically, and also, like, I'm trying to add some sort of repulsion behavior for the candidates. Like, people who have a lot of subjects pass. I mean, if they're passing a lot of subjects, they try to flock together. Okay. And people who have failed, they try to flock together. And people who have passed and failed try to repulse each other. I'm trying to figure that out using processing. Cool. Sounds good. So, you're using processing? Yeah. Is that something that you can like take a peek? Not exactly. I'm trying to figure out certain examples right now, but I'm having some errors in it. Your name and what you're doing for the evening? My name is Pramod. So, evening, I'm working with Suraj here. We are taking some data from B-Wall. Okay. And they have some 8 million reviews of social, you know, movies and restaurants and what else. A bunch of social reviews. All web crawls. Yeah, I guess. So, we are just planning to use Hadoop to extract data out of it in various ways. Okay. We are pretty much newcomers to the thing that you want to hack. Okay. Cool. How do you feel coming to the hack night? Oh, it's good. I think it's really nice. And I hope to meet interesting people out there. Okay. Good luck. Your name and what you guys are doing for the evening? So, I'm Vikrant. This is Muthi. We are trying to, we are analyzing Wikipedia data. Okay. We are trying to analyze the relationship between different entities. All right. So, can you tell me a bit more about the tools that you are using? So, pretty much the standard stack. Standard stack. Standard stack. That's fine. Okay. Good. Great. Cool. Good luck then. Yeah. Thank you. My name is Zunak. Gaurav. Gaurav. We are working on a challenge on Kaggle where we are trying to predict what will be, what are the blockbos a user is likely to like. Okay. So, what is the history of liking certain blogs and blockbos? All right. Your name and what you are doing this evening? Just quickly. Yeah. Shantanu, you are trying to work with Twitter data. Okay. So, what exact point do you have in your name? Yeah. Just working with Twitter data and let's see what comes up. So, what are the kind of tools that you are using? Right now, we are thinking of using some, post the export. We plan to use some processing data, but nothing in mind yet. Cool. Good luck. Yeah. Thank you. Yeah. Hey guys, I am Resin and I am working on a Twitter data set. So, what we thought first was to build a sentimental kind of analysis on that. And we are struggling with that right now. Basically, the guy is sitting over there. He is going to build a classifier and have to give him data for that. Okay. So, it is a little tough because we are hitting APIs and rate limits. So, what we thought is we just start out with smileys. And search for smileys in data and assume that they are happy, sad stuff. And thought we built from there. Cool. Let's see how it goes. Good luck. Thanks.