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You are correct about AI which includes ML which includes DL. NN can indeed be included in ML, be it inside or outside of the DL context. An example for the latter is when neuronal nets are used in simple task based learning (e.g. recognize car number plates in pictures). Data mining is somewhat broader than your definition, because it's not only ...


3

Here is the general approach: Read a dictionary file and organize all words in a trie data structure. Many Unix systems have such files in the /usr/share/dict/ directory. Find possible matches of a prefix of your input in the trie. This will usually produce multiple matches, for example theologyisabout begins with theology and the. If we remove the matched ...


3

You might be looking for Pareto efficiency/optimality. This will allow to select only pairs that are not worse than anything else. From those, you can then pick those that are best for you. The major advantage of this algorithm is that it can be applied for more than two variables.


2

First, you need to define some sort of evaluation function that can tell you the value of a given combination. For example, are you trying to maximize price per square foot? Square feet per dollar? Something else? Once you have such an evaluation function, simply calculate the result for each combination of factors in your dataset and then select the ...


2

Quite simple really - Firstly represent each user with a uid, and each track in the list as a song id. You will now have your user / item matrix representation. For each user in your dataset run jaccard similarity. It's very simple, it just looks at intersections of songs between users. Then take the X most similar users which can form the users ...


2

I would recommend using Chrome for this. The inspect and debugging tools allow you to view the js source files along with the html and css. Steps: Right click on the element in question in Google Chrome. Click inspect element which is the last item in the menu. The developer menu will popup in the bottom of the screen. The html for the selected element ...


2

A brilliant introduction to the concepts of data mining and statistical analysis can be found in Gordon Linoff's Data Analysis Using SQL and Excel book. This is a great book if your background is in data warehousing, data analysis or business intelligence


1

My recommendation is to pick up Python. There are lots of tutorials to get you going, and there are TONS of examples on how to scrape websites using tools like BeautifulSoup, and if you found a JSON api then you can grab it using tools like "requests". Then you can schedule your program to run daily using tools like cron if you are under Linux. On Windows ...


1

There are two problems in this. Firstly storing results (in database or in cache etc.) so that the calculations does not have to be remade every time a page is loaded. Secondly you need a mechanism to redo all calculations, you could have found a flaw in an old calculation or old data is updated/purged or new calculations are added. The best way to do ...


1

You probably want to look into the Double Metaphone phonetic algorithm, which is designed to handle how words are pronounced in different languages. There is also a Metaphone 3, but that costs money to use.


1

First, I'd recommend a better data structure for your transactions. Whereas a binary tree is preferable to a sequential list (assuming the list is more than about 10 items), it's still log(n) to find an item. Your code would execute a whole lot faster if your store receipt stored the items in a hash table rather than in a binary tree. Rather than O(n log(t)),...


1

Thought I'd answer my own question here with my final solution. I realized that although I could get some partially meaningful data from k-means clustering of RGB values, the problem was that the recommendation was not based on meaningful characteristics of the image. It could potentially be useful in the future for other aspects (such as lighting or "...


1

There are a number of collaborative filtering methods you can research. As an alternative, I'm going to suggest something very pedestrian instead that should be easy to code and should give you reasonable results. Caveat: This is just off the top of my head, and may be very inferior to some of the more established methods out there, but it seems like a fun ...


1

I would treat the DateCreated column from entity A and entity B as a foreign key to another table that stores counts of A and B for those dates. You can drop the seconds for that foreign key. You can then use that table to find all entity A records that have entity B records within X minutes of each other. That would be done by using a JOIN from the entity ...


1

Well, your basic algorithm sounds to be like this (in C#, but that does not really matter): bool DoFullSearch(List<Transformation> transformationList, SearchData originalData) { foreach(var transformation in transformationList) { var transformedData = transformation.Apply(originalData); bool success=DoSingleSearch(...


1

I'm not sure what language you are using, but I would create a some objects/functions that can perform the transformation of the song data. I would pass these objects/functions to a transformation consumer. The consumer takes the lyrics,artists,etc. and loops over the transformation functions, each time passing in the lyrics,artist,etc., and then querying ...


1

One technique that can be used to perform clustering on multi-dimensional numeric data is the Kohonen self-organising feature map. It's a little too involved to describe here, but should be included in any beginner's level text on machine learning. This just leaves the problem of how to convert your data to numeric form. To do this, I'd first run an an ...


1

I know that there is some research in the area of social network analysis to large software projects with regards to both knowledge management as well as the identification of defects, but to the best of my knowledge, it's mostly academic at this point. I did find Supporting Collaborative Software Development through the Visualization of Socio-Technical ...


1

This is a perfect application for a full-text indexer such as Lucene. Let's say your questionnaire asks about three things: smoking, diabetes and obesity. Once the text of the articles is indexed, you can use the answers you get to form queries that will return the most relevant articles first. So, for example, the query for an overweight, non-diabetic ...


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