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In our project we use Stochastic Gradient Descent (after CountVectorizer, TfidfTransformer) for classify messages The customer new in ML, so he want to understand (how) why model relates a message to some category. Could you please give suggestions for explanation, of course, without math?
first and foremost if your customer is not from technical background , then never use technical terms in front him. by using technical terms , you are making situation even more worse because he is into new thing and he is confused with your jargon. so never make someone freak out .!!
give him simple examples :
like " Recommending music on gaana.com , saavn.com " or " Recommending Movie on NetFlix " :
tell him/her " how a machine will understand what is your like and dislike ? ". or even how you will get to know my music liking and disliking ? can you ?
by finding my favorite. right !!
how you get to know this my favorite ? Either by asking me !! or looking into my most top rated or more liked or you heard i always listen some common songs !!
Exactly this above process you followed is called " finding pattern in Machine Learning " and using this method machine able to recommend new songs, movies, ..etc.
i'll also suggest don't explain above thing . because your customer is not that much dumb who is dealing with your work/product !!
give him real time use cases.. like recommendation process , or in social media recommending friends !!.. and many more...
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I'm doing software engineering and I'm learning Artificial Intelligence course in the current semester, then I need to give the project at the end of this semester (after 3 months). So, my question is which project is recommended for me, voice expression AI project or face expression AI project?
VOICE EXPRESSION: This software will listen user's conversation whole day then at the end of the day, it will show that how many bad words the user spoken, for how much time user got hyper, for how much time user got angry, etc.
FACE EXPRESSION: This software will monitor the screen of computer (for example teacher delivering lecture on ZOOM and camera of students are opened) then it will tell the user(or teacher) who is taking interest in user's lecture, who is confused, who wanna ask question etc.
So, If I'm a beginner in AI what project should I choose from those two projects? or should I choose easy project other than those two projects?
In principle, voice analysis seems to me easier than face analysis. To begin with, there is only one dimension, rather than two, and it would probably be easier to recognise words in a stream of sound than faces in a stream of images. However, I have a background in phonetics/signal processing, so sounds do look easier to me than images. If you've done image processing before, that might be better suited for you.
The key for a good project should not necessarily be how easy or hard it is, but whether it is something you are (a) interested in, (b) capable of achieving, and (c) relate to the course.
Also, be clear about what you want to achieve and how easy that is to determine: matching the sound pattern of a word is something much more objective than trying to identify if someone is bored or wants to ask a question based on facial expressions.
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I need to write the backend for an event ticket selling system. Some companies would connect to the service in order to check for ticket availability in certain venues, book tickets and so on.
Reading about Erlang I though it could be a good choice since the system will have to support high concurrency, high availability but I don't know If it's a good choice for this problem domain.
Any help would be really appreciated. Thanks!
Erlang could be a good choice, yes, it sounds like something it would do a very good job.
But it's going to be hard for anyone here to be of much value for your decision, as you should also consider the knowledge level of the team, time & budget constraints, etc.
Ultimately, the best people to help you make this decision are the people in your team.
I suggest you take a look at OTP's finite state machines as I think it suits perfectly a ticket booking system.
I believe you can find a lot of examples either in the doc or on the web.
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I have a decent amount of programming experience, and I just do not know where to start to learn this.
I've done the tutorials on apple's site, and looked at some other examples, but there is just so much stuff you need to know, that I'm feeling kind of lost.
I understand the whole MVC thing, I understand and know objective c, I just know all the general stuff, but when writing an app I just miss a lot of knowledge and I'm constantly unsure about how to do certain things.
Is it just a matter of keep going at it? Are there any really good books? Any really good online resources?
And again: it's really about just getting to know the ins and outs of all the frameworks and different objects and stuff
For someone in your position, the two words you need to know are Ray and Wenderlich.
For beginners I would really recommend to watch Paul Hegarty's Stanford iPhone development courses.
See:
https://itunes.apple.com/us/itunes-u/developing-apps-for-ios-hd/id395605774?mt=10
His courses are one of the most clear and effective courses I've ever seen.
EDIT:
New (iOS 7 courses):
https://itunes.apple.com/si/course/developing-ios-7-apps-for/id733644550
Watch few intro videos, read few intro articles. Plenty of them online. And build something. Repeat.
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The single most effective thing I have done to improve my soft skills is to take an acting class.
What is the single most effective thing you have done to improve your soft skills?
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What is the single most effective
thing that you have done to improve
your programming skills?
Advice
to improve programmer communication
skills
Better appreciating just quite how dumb I really am.
Starting from the perspective of assuming that you're misunderstanding what's going on helps a lot.
Started answering questions here - the ability to explain complex things in a way other people can understand them is very useful.
Not to be a smart-arse. People don't like smart-arses.
If you think you are right and everyone else is sure you are wrong, just agree and continue being right. Trying to argue it out just results in a negative outcome when people are not open to persuasion or are being stubborn.
The best way to improve your soft skills is to use your soft skills. Put on a lunch time seminar for your fellow work mates. Nothing too scary, just pick a technology that you think could be introduced in house to make things work more efficiently, put together a five minute presentation and set some time aside for questions and discussion afterwards. You might even start a trend, one day a week a different person can talk about something that interests them.
It's a tie between volunteering as newsletter editor for a local artists' group, and joining a small local theatrical dance group.
A few years ago I attended a workshop about communication. And one thing that I learned there and I will never forget was: Try to understand why people act as they act, try to understand their motivation doing things as they do. That helped me a lot, especially in managing the management...
I took a teaching course and have been doing a lot of teaching.
Where I work currently has some material about improving one's Emotional Intelligence which is something that has been quite beneficial for me as it helps demystify some of how the world works.
In terms of not learning something, working on making small talk and being a bit more laid back has also improved my skills as not everyone wants every little thing analyzed to death and beyond.
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Twitter, Google, Amazon, del.icio.us etc. all give you a lot of data to play with, all for free. There's also a lot of textual data available through initiatives like Project Gutenberg. And that, it seems, is just the tip of the iceberg.
I have been wondering how you could use this data for fun. I'm a first year IT student, so I have no knowledge of statistics, machine learning, collaborative filtering etc. My interest in this area was piqued by the book Programming Collective Intelligence by Toby Segaran, and now I want to take a deeper look at what you can do with data. I don't know where to start. Any ideas?
I have also been pondering whether I should go and buy something like Paradigms of Artificial Intelligence Programming. Is it worth the trip across the city?
Try firing books in different styles from Guttenberg through a Markov Chain generator - there's one in Perl here to get you started.
Visualizations, do them, share them.
You can use some of that data to make money (if you're really good!)
http://www.netflixprize.com/ Netflix has made available an anonymized dataset, and are asking for better algorithms to predict customer choices.
If you're familiar with Python try playing around with the nltk. It has tons of libraries for text mining and even machine learning in general. Try working your way through nltk book.
If you want to start off with a easy AI problem, you might try clustering.
http://en.wikipedia.org/wiki/Data_clustering
You could use it to group flickr images together by tag or something cool like that.
You can make puzzles like hangman games. Or a mashup or try Yahoo pipes to join information.
Predict future stockmarket trends from the data. Profit!