Search results
Results From The WOW.Com Content Network
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] 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 ...
scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language. [2] It includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more. [3]
Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.
Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats.
The scikit-learn project started as scikits.learn, a Google Summer of Code project by David Cournapeau. After having worked for Silveregg, a SaaS Japanese company delivering recommendation systems for Japanese online retailers, [3] he worked for 6 years at Enthought, a scientific consulting company.
Download and install the latest Java Virtual Machine in Internet Explorer. 1. Go to www.java.com. 2. Click Free Java Download. 3. Click Agree and Start Free Download. 4.
scikit-learn, a library for machine learning. TomoPy, a package for tomographic data processing and image reconstruction; Veusz, a scientific plotting package; VisTrails, a scientific workflow and provenance management software with visual programming interface and integrated visualization (via Matplotlib, VTK). Apache Singa, a library for deep ...
Keras contains numerous implementations of commonly used neural-network building blocks such as layers, objectives, activation functions, optimizers, and a host of tools for working with image and text data to simplify programming in deep neural network area. [11]