Python frameworks for data science
There are many frameworks available in python for scientific computing/calculations...
Some of these are as follows:-
NUMPY:-Numpy is an array manipulation library build on the top of python programming language it is easy to use and handle and it can be directly installed using pip package manager.
PANDAS:-Pandas is a Data manipulation framework build on the top of python programming language you can very easily connect to a spreadsheet document using this.
MATPLOTLIB:-Matplotlib is rich graphics and Drawing tool/framework available in python.It can considered as a replacement of MATLAB language.
SCIKIT:-Scikit-learn (formerly scikits.learn and also known as sklearn) is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.
OPENCV:-OpenCV is a computer vision library for python which is used for image detection and classification.
TENSORFLOW:-It is a Machine Learning Framework for python.It is very easy to learn and understand.It is very popular as it is known as a 'Google product'.
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