Friday 26 April 2019

Python and Data Analysis: A closer look


Mlpy
Built on top of NumPy and SciPy, mlpy features a range of machine learning methods for both supervised and unsupervised problems. This is also multiplatform, which works with Python 2 and 3.

SciPy
Similar to data libraries you use when you look for “help with my thesis”, SciPy is well-known and widely used in the scientific and technical computing field. It has modules on linear algerbra, optimization, integration, special functions, FFT, interpolation, and other tasks common and necessary in science and engineering.

NumPy
This one is an open source extension module, which provides precompiled functions for numerical routines. It also adds support to Python for multidimensional arrays and matrices. Moreover, it supplies a huge database of high-level mathematical functions, specifically to operate on the arrays.

matplotlib
This one is a plotting library for NumPy, which provides an object-oriented API for embedding plots into applications. It makes use of general-purpose GUI toolkits such as Gt, GTK+, and wxPython.

Theano
This Python library allows you to optimize, define, and also evaluate mathematical expressions effectively, which involve multidimensional array.

NLTK
The NLTK, or the Natural Language Toolkit, is a database of libraries and programs statistical natural language processing (NLP). It utilizes graphical demonstrations and sample data. It has also been used as a platform for building and prototyping research systems

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