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Monday, October 30, 2017

डॉट नेट में मशीनी अधिगम प्रणाली निर्माण

परिचय और आरंभिक प्रोग्राम के उदाहरण द्वारा इस प्रकार से समझ सकते हैं-
(Datahub से साभार)

What is machine learning?

If you check out on Wikipedia, you will find a fairly abstract definition of machine learning:
“Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions, rather than following strictly static program instructions.”
I like to think of machine learning as computer programs that produce different results as they are exposed to more information without changing their source code (and consequently needed to be redeployed). For example, consider a game that I play with the computer.
I show the computer this picture  and tell it “Blue Circle”. I then show it this picture  and tell it “Red Circle”. Next I show it this picture  and say “Green Triangle.”
Finally, I show it this picture  and ask it “What is this?”. Ideally the computer would respond, “Green Circle.”
This is one example of machine learning. Although I did not change my code or recompile and redeploy, the computer program can respond accurately to data it has never seen before. Also, the computer code does not have to explicitly write each possible data permutation. Instead, we create models that the computer applies to new data. Sometimes the computer is right, sometimes it is wrong. We then feed the new data to the computer to retrain the model so the computer gets more and more accurate over time—or, at least, that is the goal.
Once you decide to implement some machine learning into your code base, another decision has to be made fairly early in the process. How often do you want the computer to learn? For example, if you create a model by hand, how often do you update it? With every new data row? Every month? Every year? Depending on what you are trying to accomplish, you might create a real-time ML model, a near-time model, or a periodic model.

Why .NET?

If you are a Windows developer, using .NET is something you do without thinking. Indeed, a vast majority of Windows business applications written in the last 15 years use managed code—most of it written in C#. Although it is difficult to categorize millions of software developers, it is fair to say that .NET developers often come from nontraditional backgrounds. Perhaps a developer came to .NET from a BCSC degree but it is equally likely s/he started writing VBA scripts in Excel, moving up to Access applications, and then into VB.NET/C# applications. Therefore, most .NET developers are likely to be familiar with C#/VB.NET and write in an imperative and perhaps OO style.
पूरा पढ़ने के लिए इस लिंक पर जाएँ-
https://datahub.packtpub.com/tutorials/welcome-to-machine-learning-using-the-net-framework/

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