Useful python Libraries for Machine Learning Projects #3

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1.Keras

Keras is a one of the excellent Python libraries for machine learning. It makes expressing neural networks easier along with providing some of the best utilities for compiling models, processing data-sets, visualization of graphs and more.

2.Numpy

Numpy is another popular machine learning python library. It is easy to used, interactive and quite intuitive.  It makes complex mathematical implementations very simple.  Numpy can be used for expressing images and sound waves and other binary raw streams in the form of an array of real numbers in 1 N – dimension.

3.TensorFlow 

Tensor flow is an open source Python Library Developed by Google and collaboration with Brain Team.  Tensor Flow is used for writing new algorithms that include a large number of tensor operations.  As neural network can be easily expressed as computational graph, they can be implemented as a series of operations.

4.Scikit – Learn 

skit – Learn Scarcities one of the most useful Python’ libraries for working with complex data. Its associated with NumPy and snippy and comes with many useful features.

5.PyTorch 

PyTorch is one of the best popular machine libraries known for its extensive features. Its based on Torch, an open-source machine’ library implemented in C with a wrapper in Lua.

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