Keep Yourself Updated About Machine Learning With These Top Open Source Libraries

The key premise of Machine Learning is to create algorithms that are able to receive the input from the user and use the Statistical Analysis methods to predict an appropriate output.

Machine Learning has now been among named among the mainstream technologies that are playing a major role in shaping our daily activities routine. There are many factors that make machine learning so approachable and further to be used by app developers.

And one of these contributing factors is the ‘Framework’ and below are the top Open Source Libraries that comes to your rescue when dealing with Machine Learning:

  • AML stands for Amazon Machine Learning, one of the wide-known machine learning resource. A developer is able to generate predictions with the help of AML and use the data from the data warehouse Platform-as-a-Service i.e., Amazon Redshift.
  • If you are looking for a .NET machine learning framework with multiple libraries to efficiently maintain Image/Pattern Recognition, Signal Processing, Statistical Data Processing and Linear Algebra as well then you need Accord.NET to handle it all.
  • Developed by one of the Google Team, TensorFlow is here to handle the language understanding and other perceptual tasks effectively. The TensorFlow has a Python-based Interface which can be used for Gmail, Speech Recognition as well as Search.
  • Shogun is an open source library that basically has many State-of-Art algorithms which makes it a great tool for the developers. Another reason why Shogun is favored is that it supports bindings to other machine learning libraries as well.

Sometimes the frameworks and libraries can be confusing to many people. That is why the App Development and App Design Companies are spreading awareness through their technical blogs regarding the latest technologies and their tools.

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