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    How Machine Learning works with Python?

    Machine learning is a subset of Artificial Intelligence wherein a machine is made to learn with a set of data to achieve a specified objective. In this whole process, it is very important the data integrity is kept to the best possible quality level as output of machine is primarily dependent upon that. Machine learning has intersection with Mathematics and Psychology.  In programming world there are many languages through which Machine learning objectives can be developed, viz. C, R, Prolog, Java and Python.

    Over the years, Python as a programming language has gained lot of popularity due to its high flexibility, simplicity and multi purpose uses.Python contains special libraries for machine learning namely scipy and numpy.

    NumPy is a fundamental package for scientific computing with Python. It is a general-purpose array-processing package which provides a high-performance multidimensional array object, and tools for working with these arrays.

    The key features contained are:

    Useful linear algebra, Fourier transform, and random number capabilities
    A powerful N-dimensional array object
    Sophisticated (broadcasting) functions
    Tools for integrating C/C++ and Fortran code

    These are great for linear algebra and getting to know kernel methods of machine learning. The language is great to use when working with machine learning algorithms and has easy syntax relatively. For beginners, this is the best language to use and to start with.

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