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This might not be the right place for this to ask, but I am interested in artificial neural networks and want to learn more.
How do you design a network and train it on source code so it can come up with programs for, for example, easy number theory problems?
What's the general name of this research field?
This is a hugely interesting, and very hard, problem area. It will probably take you months to read enough to even understand how to attack the problem. Here's a few things that might help you get started, and they are more to show the problems you will face than to provide solutions:
http://karpathy.github.io/2015/05/21/rnn-effectiveness/
Then read this, and related papers:
https://arxiv.org/pdf/1410.5401v2.pdf
Next, you probably want to read the classic papers in program synthesis and generation at the parse tree/AST level (mostly out of MIT, I think, in the early 90s.)
Best of luck. This is not trivial.
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I have a paragraph, system has to understand it and it should answer all the questions asked by the user. Please name the techniques and methodologies.
It all depends on the problem that you are trying to solve, the data available to you and the underlying domain. Lets get to it one by one:
Type of Problem
There are multiple types of question answering systems, like one word answers based on extract the exact answer from various sentences, or returning the most similar sentence from a list of sentences based on the question asked by the user, using various similarity and embedding techniques. I think this paper : Teaching Machines to Read and Comprehend should be a good place to start getting an idea about such systems.
Dataset
Next comes the dataset for such systems. Now there are various datasets available for question answering systems like :
SQuAD dataset
QA dataset based on Wikipedia Articles
Facebook bAbI dataset
AllenAI dataset based elementary Science question
NewsQA datset
Methodologies
Well there are multiple ways to go about solving this problem. It would be difficult to list all of them in one answer, but I can provide you some references:
Deep Learning for Question Answering
Various Deep Learning models on Question answering
SquAD dataset Leaderboard
Question Answering based on Word Alignment
Attention Based Question Answering
Reasoning-based QA
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I would like to interpret problem on picture below, which is about perceptron learning. It is about supervised learning wiht a training set, so correctness of values should be checked against a predefined set of values. I don't exactly know, how A, B and bias(b) values come. Could you please explain meaning of these and how these computed and changed during the learning process?
Here you have an intuitive, visual, interactive and beautiful guide to the basics concepts of neural networks:
https://jalammar.github.io/visual-interactive-guide-basics-neural-networks/
It will problably solve all your doubts. However, if you still have more questions after the reading, you will be able to ask something more specific. Enjoy!
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(homework problem)
Which of the following problems are best suited for the learning approach?
Classifying numbers into primes and non-primes.
Detecting potential fraud in credit card charges.
Determining the time it would take a falling object to hit the ground.
Determining the optimal cycle for trafic lights in a busy intersection
I'm trying to answer your question without doing your homework.
Basically you can think of machine learning as a way to extract patterns from data where all other approaches fail.
So first clue here: If there is an analytic way to solve the problem then don't use machine learning! The analytic algorithm will likely be faster, more efficient, and 100% correct.
Second clue is: There has to be a pattern in the data. If you as a human see a pattern, machine learning can find it too. If lots of smart humans who are experts of the respective domain don't see a pattern then machine learning will most likely fail. Chaos can not be learned, i.e. classified/predicted.
That should answer your question. Make sure to also read the summary on wikipedia to get an idea whether a problem can be solved using supervised, unsupervised, or reinforcement learning.
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Using data mining, we are able to find useful patterns in a large set of data using techniques like correlation etc etc and there must exist some open source tools for this (what are some examples?).
Is this pull-based or push-based? I mean, do we provide data set as well as specific queries as input to the data mining engine and it provides us answers (as in SQL) or we only supply large data set as input to the engine and it on its own find patterns (which we never knew existed and/or we couldn't formulate queries for this) and thus we don't really pull any specific queries from it, it pushes the patterns to us.
Some quick reading of Wikipedia article doesn't clarify my doubts in clear way.
As open source have a look at Weka.
In regards to the push-pull thing, well, it's a bit of both. But it's not quite that simple. You must be looking for something. E.g. if you are looking for clusters, there are unsupervised algorithms which will give you an answer with minimal guidance.
In practice things are more meaningful if you know about the data you analyse and you are looking at regularities and patterns that make sense.
Playing with Weka will give you a better idea of the range of possibilities.
Python and R are other great open source tools that have great popularity in the data mining area.
A great tool that i used recently is scikit-learn
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My company has been using FogBugz for a while now and we are generally happy with it as a bug-tracking tool. I've been reading Joel Spolsky's articles about their Evidence Based Scheduling feature. It sounds great in theory, but I haven't seen much discussion about how well it actually works in practice. Before I spend a lot of time and effort trying to convince my co-workers to buy in to using it, I'd like to hear from people who have been using this feature in their development.
Have you been using FogBugz' EBS? If so, are you happy with it? Have its estimates been accurate enough to be helpful? With the benefit of hindsight, do you think it was worth the effort to set it up and input all of the information/estimates it requires? Is there some other mechanism that you found that works better?
(Note: I've deliberately posted this to stackoverflow.com rather than fogbugz.stackexchange.com, since I suspect that the user base at fogbugz.stackexchange.com might be unduly biased in favor of FogBugz -- in particular, ex-Fogbugz users who've moved on to something better are unlikely to read or post there)