The SciPy ecosystem for scientific computing

Widely used by data scientists when developing Artificial Intelligence data models!

The SciPy ecosystem is a collection of open source software for scientific computing using the Python programming language providing efficient routines for numerical optimisation.

supervised machine learning


Python is a general purpose programming language widely used by data scientists when developing Artificial Intelligence data models (these models are used to "train" computers to "learn" for themselves).

NumPy is the fundamental package for scientific computing with Python and defines numerical arrays and matrix types and performs basic operations and provides useful capabilities such as linear algebra and generating random numbers.

Pandas (Python Data Analysis Library) is an open source software library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

SymPy is a Python library for symbolic mathematics. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python.

Scikit-image is a collection of high-quality, peer-reviewed algorithms for image processing.

Scikit-learn is a collection of algorithms and tools for machine learning.

See SciPy Website