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Project Jupyter ( / ˈdʒuːpɪtər / ⓘ) is a project to develop open-source software, open standards, and services for interactive computing across multiple programming languages . It was spun off from IPython in 2014 by Fernando Pérez and Brian Granger. Project Jupyter's name is a reference to the three core programming languages supported ...
Mojo. Mojo is a programming language in the Python family that is currently under development. [ 2][ 3][ 4] It is available both in browsers via Jupyter notebooks, [ 4][ 5] and locally on Linux and macOS. [ 6][ 7] Mojo aims to combine the usability of higher level programming languages, specifically Python, with the performance of lower level ...
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Codelobster, a cross-platform IDE for various languages, including Python. EasyEclipse, an open source IDE for Python and other languages. Eclipse ,with the Pydev plug-in. Eclipse supports many other languages as well. Emacs, with the built-in python-mode. [1] Eric, an IDE for Python and Ruby.
Anaconda is a distribution of the Python and R programming languages for scientific computing ( data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS.
Notebook interface. A notebook interface or computational notebook is a virtual notebook environment used for literate programming, a method of writing computer programs. [1] Some notebooks are WYSIWYG environments including executable calculations embedded in formatted documents; others separate calculations and text into separate sections.
TensorFlow.nn is a module for executing primitive neural network operations on models. [ 38] Some of these operations include variations of convolutions (1/2/3D, Atrous, depthwise), activation functions ( Softmax, RELU, GELU, Sigmoid, etc.) and their variations, and other operations ( max-pooling, bias-add, etc.).
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 ...