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Keras allows users to produce deep models on smartphones (iOS and Android), on the web, or on the Java Virtual Machine. [8] It also allows use of distributed training of deep-learning models on clusters of graphics processing units (GPU) and tensor processing units (TPU) .
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 ...
Mirfak is an open-source mod_frontpage reimplementation that is more secure, and can be used with a binary installation of Apache (possibly including mod_ssl, php, etc.). The module is licensed under the Apache license. mod_geoip: Version 2.0 and above: Third-party module: MaxMind: Apache License, Version 1.1: Looks up the IP address of the ...
1. Go to www.java.com. 2. Click Free Java Download. 3. Click Agree and Start Free Download. 4. Click Run. Notes: If prompted by the User Account Control window, click Yes. If prompted by the Security Warning window, click Run. 5. Click Install, and then follow the on-screen instructions to complete the installation. You're done!
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 ...
Soon after, the Python and R packages were built, and XGBoost now has package implementations for Java, Scala, Julia, Perl, and other languages. This brought the library to more developers and contributed to its popularity among the Kaggle community, where it has been used for a large number of competitions. [11]
[7] [8] [9] The initial version was released under the Apache License 2.0 in 2015. [1] [10] Google released an updated version, TensorFlow 2.0, in September 2019. [11] TensorFlow can be used in a wide variety of programming languages, including Python, JavaScript, C++, and Java, [12] facilitating its use in a range of applications in many sectors.
Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.