So I am working on a Machine Learning project of rainfall prediction. For now I am working on visualizing the data I have. So, I have daily rainfall data from 1951 - 2007 for 84 different weather sites. So now given some particular year and month I want to plot a heatmap of average rainfall during that month and year across different sites. Also this heatmap should be plotted on a geological map. What is the best approach to build such plots. It'll be better if someone can suggest me any already existing library.
To get started quickly, try PowerMap for Excel.
https://support.office.com/en-us/article/Get-started-with-Power-Map-88a28df6-8258-40aa-b5cc-577873fb0f4a
http://geoawesomeness.com/geoawesomehowto-how-to-make-a-killer-map-using-excel-in-under-5-minutes-with-powermap-plugin/
Even if that doesn't meet your needs completely, you should be able to test ideas quickly.
Related
Apologies in advance if this is a dumb question. Is there fairly straightforward way to write an app that will use the Camera (for example iOS) to take a photo of a pre-formatted screen and recognize / retrieve that data?
This isn't a top secret project or anything, so I'll be happy to share as many details as necessary. Basically my electric car displays a pop-up with stats when it turns off. Since there aren't any OEM apps that track things like charging, I guess I have to do it manually. I figured, since the screen is always the same, perhaps it would be possible to aim the camera "just right" using an app that could look for certain data in certain places. The way a shopping app looks for barcodes or Apple Wallet reads credit card numbers.
Is this a dumb idea? If it's easy and you'll make a million bucks selling the app, then feel free to steal it. I'll be your first customer. In the meantime, is this doable by a random jackass who's way over his head when it comes to programming? :-)
For example, if I could just grab Energy Used and Miles driven, then I'm sure I could programmatically get other data like date/time from the device taking the picture. Here is one example.
'energy used' popup Sample screen 001.
I’m straggling to download historical data for my masters thesis. I need daily prices (only one per day e.g. adjusted close) of all companies listed in a stock exchange, specifically in Hong Kong SE, over 20 years including delisted and new starting with issuing day. Is there a way to do it with R? I am thinking about getting a list of all companies listed at every day over the past 20 years and then getting prices for that particular day and company. But I’m not sure who to put it into a code. Or maybe there is another way to do it? Perhaps with Bloomberg terminal? I got one at campus. I would very much appreciate any help.
If i well understand your question. You need to work on R and manage a database of the HonKong SE stocks. For this task, I can advise you to go to quandl.com. You can access it for free and loading stock prices in R. You just have to sign into the api and get you Key. direct link to Hong Kong page on quandl.com
I work for a research organization in India and have recently taken up with a program extending immunizations among poor rural communities. They're a fairly large organization but don't really have any IT infrastructure. Data reports on vaccine coverage, logistical questions, meeting attendance etc. come from hundreds of villages, go from pen-and-paper through several iterations of data entry and compilation, finally arriving each month at the central office as HUNDREDS of messy Excel sheets. The organization generally needs nothing more than simple totals and proportions from a large series of indicators, but doctors and high-level professionals are left spending days summing the sheets by hand, introducing lots of error and generally wasting a ton of time. I threw in some formulas and at least automated the process within single sheets, but the compilation and cross-referencing is still an issue.
There's not much to be done at the point of data collection...obviously it would be great to implement some system at the point of entry, but that would involve training hundreds of officials and local health workers; not practical at the moment.
My question: what can be done with the stack of excel sheets every month so we can analyze individually and also holistically? Is there any type of management app. or simple database we can build to upload and compile the data for easy analysis in R or even (gasp) excel? What kind of tools could I implement and then pass on to some relative technophobes? Can we house it all online?
I'm by no means a programmer but I'm an epidemiologist/stats analyst proficient in R and Google products and the general tools of a not-so-tech-averse millenial. I'd be into using this as an opportunity for learning some mySQL or similar, but need some guidance. Any ideas are appreciated...there has to be a better way!
step by step approach would be, first store the raw data from excel sheets and papers in structured database. Once data is maintained in DB you will have many tools to manipulate that data later.
Use any database like MySQL to store excel sheet ; Excel sheets or CSV files can be exported to database directly.
Later with simple database operations you can you can manipulate the data; you can use reports/web application/etc. to display and manage data.
and keep the good Work!
I need very basic help (hopefully) on an Artificial Intelligence Project. My question is very basic so I won't be getting into many details other than what is required. My question starts with a description of the problem, which is to determine the best route to change the temperature. This sounds very vague but to clear things up it is for developing a thermostat. I want to be able to properly control temperature in the most efficient way by using a variety of sensors including outside temperature, humidity, motion in the home (whether someone is home or not), etc.
An example might help as well: Lets say its summer time and the A/C is on. The setpoint is set to 77, but the temperature is 79. However, nobody is home. But the thermostat knows the user will be back home at exactly 4pm in which it is currently 1 pm. And according to weather websites, the outside temperature is going to drop to 77 at 3 pm. The humidity is very high which also plays a big factor. Should the A/C turn on? If so for how long?
My real question is what AI Technique should I look into to solve this kind of problem. I want to simulate something similar situations in python before deploying it on an Android/Java level. I am a very beginner in the area of Artificial Intelligence and want to know the quickest and best manner to approach this problem while making sure I understand everything there is to know about AI at this project level.
I'm not expert, but for this kind of issues prefer using Fuzzy Logic or Expert Systems.
You can use a neural network to predict the status of the thermostat and control it behavior which is based on several parameters. Thermal neural networks may help.
So, I've just decided to build my own fantasy sports web site.
You know the type of site where you can pick players from your favourite league and depending on how they do you get a certain amount of points in your team. There are fantasy teams for all types of leagues and sports, I'm sure you know what I'm talking about.
I haven't settled for a specific sport or league just yet because I want the basics to fit to different types of team-based sports.
I have a few expectations on it myself. If you can come up with any other I'll be glad to hear them.
I expect the site to be dynamic and have many visits during a game, but almost only static content otherwise.
Player points should be updated in real-time during a game.
I would need a list that shows each game being played and the points of every player in that game. It should also show minutes played, goals, assists etc.
Each registered user would be able to see the points and players of his/hers team updated in real time.
I need the site to scale so that if I start with 1000 teams I could end up with 5 million.
I probably won't be needing language support right now, but who knows in the future.
Based on these prerequisites what would be best to use in terms of language (php, .NET, drupal or other cms's), database (mysql, sqlserver, xml) and other techniques?
Maybe it doesn't really matter what I use?
I guess the dynamic and real time update of each player's points is where I need help the most.
Thanks in advance!
/Niklas
EDITED
I could use an array with the following data for a specific game week:
Player ID
Minutes played
Sport specific points(goals, assists, penalties, yellow cards, man of the match bonus) etc.
Total points in current game week
When the game is over I'd add these to a DB and sum this data with any previous game weeks. Plus player value, number of teams that has selected this player, etc.
You are probably going to have to go down the custom route for your "Game" code - rather than using a CMS, although depending on your experience, you may be able to leverage a framework (e.g CodeIgniter) to speed up some of your DEV time.
This type of site would be pretty language agnostic, however it would depend on the actual numbers of users you are looking at as to the most scalable solution / set of techniques to deploy.
One of the biggest considerations you are going to have to look at would be the design of the data model, and the platform that this sits on.
If you want to be processing near to realtime updates, you are going to want to focus your efforts on making the DB queries / processing the most efficient possible.
One big consideration that you have not discussed here is caching. There is some data on your site that I am sure will be static for long periods of time (such as weekly totals etc), and there is data that will be very much real time (but only during match days).
However, during match days you will have a lot more traffic than non match days, and you will therefore have a lot of requests for the same data in a short period of time. Therefore, employing a good caching strategy will save you masses of CPU power. What I am thinking of, is to calculate a player's score and then cache for 1 minute at a time, therefore each time that specific player is requested, you are retrieving from a cache, rather than recalculating each time.