Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Contact Us

Query languages—the Swiss army knife of information extraction

Text mining, the art of extracting information from text, requires the formulation of efficient queries that retrieve information based on user input. To do this, the user requires a language for writing queries. For the most basic use cases, the language operators could be regex or string search. But while regex and string search are indispensable for text mining, their utility hits a hard ceiling when semantic or meaningful search…
Read More

Wide, Bulky Data and Dimensionality Reduction

As the saying goes, “mo’ data, mo’ problems.” Well, that’s not quite the saying and that’s not quite what we mean, but it certainly is true that large data comes with some problems that need to be solved. There are two ways that data can be “big.” Traditionally, Big Data is considered large literally by its physical size in terms of the memory space it consumes. In this article, we’re…
Read More

Choosing Machine Learning Models

As we have discussed previously, machine learning approaches to modeling are just that – approaches. There are many forms of models we could use with machine learning, each with different design philosophies and quirks. When setting out to use machine learning to create your own models, a question you may be asking yourself is: Which model framework do I choose? From Neural Networks, to Support Vector Machines, to Decision Trees,…
Read More

What’s the News with Neural Networks?

There are many reasons for the explosion of machine learning advancements over the past decade. We now have vastly improved hardware for fast computation, and memory is cheaper than ever. Data is now “Big Data,” and it is both jealously hoarded and publicly available in repositories such as ImageNet. Individually, these advancements are already a blessing for the technology-space. But for artificial intelligence (AI), they have opened the gates for…
Read More
Menu