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Hey guys, I know I've been absent from Orbiter itself for a long time, but I'm working on that. But I still poke around here and hope to get back into flights and dev work one day. So with that, I know neural networks have been a topic around these parts a number of times so I'm hoping someone can point me in the right direction.
I have two problems, one is a simple time-series prediction, I get a list of numbers (time interval is irrelevant), and I'd like to predict the next one in the series. Ideally, I'd get some kind of probability back rather than just a single number. From the research I've done, Long Short-Term Memory seems to be the way to go, but I haven't found great examples that I can go off of. I'm most experienced in .NET, but I was poking around in JavaScript the other day trying (and largely failing) to implement a TensorFlow solution. The example here would be my church's kid's program's attendance. It'd be nice to help schedule volunteers if we had a better idea what the next week's attendance will be.
The second problem is a time-series pair problem. I already have a something, and I want to predict the most likely number (again, a probability) associated to that number. The real world example would be after-church events. Let's say problem #1 predicts 50 kids this week. Given 50 kids, how many are staying after church?
So between the two problems, I already have data that looks like this (but lots more):
Week, Attendance, After-Church attendance
1, 51, 23
2, 48, 14
3, 65, 25
4, 56, 28
The output I'm going after I think would hopefully be something like Attendance: 50-55 80%, 55-60 70% ... and same for after-church attendance.
Can anyone point me in the direction of good resources online, or a good book? Looking up "neural network" on Amazon or Barnes and Noble yields lots of results and I'd rather not sink money into something blind, and I have about 18 tabs open right now from different search results so the internet isn't great either. This isn't an assignment per-se, we already do some rough statistics, like averages in our spreadsheets, but I think it'd be fun to do more, plus, it'd be a good intro into Neural Networks for me!
Thanks!
I have two problems, one is a simple time-series prediction, I get a list of numbers (time interval is irrelevant), and I'd like to predict the next one in the series. Ideally, I'd get some kind of probability back rather than just a single number. From the research I've done, Long Short-Term Memory seems to be the way to go, but I haven't found great examples that I can go off of. I'm most experienced in .NET, but I was poking around in JavaScript the other day trying (and largely failing) to implement a TensorFlow solution. The example here would be my church's kid's program's attendance. It'd be nice to help schedule volunteers if we had a better idea what the next week's attendance will be.
The second problem is a time-series pair problem. I already have a something, and I want to predict the most likely number (again, a probability) associated to that number. The real world example would be after-church events. Let's say problem #1 predicts 50 kids this week. Given 50 kids, how many are staying after church?
So between the two problems, I already have data that looks like this (but lots more):
1, 51, 23
2, 48, 14
3, 65, 25
4, 56, 28
The output I'm going after I think would hopefully be something like Attendance: 50-55 80%, 55-60 70% ... and same for after-church attendance.
Can anyone point me in the direction of good resources online, or a good book? Looking up "neural network" on Amazon or Barnes and Noble yields lots of results and I'd rather not sink money into something blind, and I have about 18 tabs open right now from different search results so the internet isn't great either. This isn't an assignment per-se, we already do some rough statistics, like averages in our spreadsheets, but I think it'd be fun to do more, plus, it'd be a good intro into Neural Networks for me!
Thanks!
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