By Mathias Brandewinder
Computer studying tasks for .NET builders indicates you the way to construct smarter .NET functions that examine from info, utilizing easy algorithms and methods that may be utilized to quite a lot of real-world difficulties. you are going to code each one venture within the known environment of visible Studio, whereas the laptop studying good judgment makes use of F#, a language superb to computer studying purposes in .NET. in case you are new to F#, this publication provides you with every thing you want to start. if you are already accustomed to F#, this can be your probability to place the language into motion in a thrilling new context. alongside the best way, you will examine basic principles that may be utilized in all types of real-world contexts and industries, from advertisements to finance, drugs, and medical learn. whereas a few computer studying algorithms use really complex arithmetic, this ebook makes a speciality of easy yet potent methods. in case you take pleasure in hacking code and information, this publication is for you.
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Machine Learning Projects for .NET Developers
Desktop studying tasks for . internet builders exhibits you the way to construct smarter . web functions that examine from information, utilizing basic algorithms and strategies that may be utilized to a variety of real-world difficulties. you are going to code every one venture within the general environment of visible Studio, whereas the computer studying good judgment makes use of F#, a language preferrred to computer studying purposes in .
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Sample text
Is that a reasonable assumption? Maybe, maybe not. If you have spent a minimum of time in online discussions, such as forums or YouTube comments, you will probably agree that A HEAVY USAGE OF CAPITAL LETTERS often indicates that the discussion quality is going downhill. So the argument can be made that capitalization matters and could provide relevant information for classifying messages. ”; is that reasonable? Punctuation could matter. The good news is, rather than argue over whether capitalization or punctuation matters, we can settle that question very easily with cross-validation later on.
One of the main reasons why I love discriminated unions is because they work so well with pattern matching and allow you to write code that describes your business domain in a very clear fashion. For instance, in our case, each example in our training set is either Ham or Spam and contains text, the contents of the actual message. info Chapter 2 ■ Spam or Ham? This example is strictly for illustration purposes, but shows the pattern we are going to follow later on. In this case, we created a small function that took in an example and printed out its contents, and whether it was Ham or Spam.
A more “correct” model would likely be specific to a particular language (taking its grammar and syntax into account, for instance), and presumably would not work on other languages. So, let’s start with a model that is pretty bad, but should be similarly bad for any language or type of document, but is easy to work with, and let’s see where that leads us! Simplified Document Score At this point we are almost ready to dive into code and implement the classifier. info Chapter 2 ■ Spam or Ham? Before jumping in, let’s make a few final adjustments.