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Comparison of machine learning model compatibility. further explanation needed] Format name ... Common platform TensorFlow, Keras, Caffe, Torch: Algorithm training No
C# can be used to develop high level machine learning models using Microsoft’s .NET suite. ML.NET was developed to aid integration with existing .NET projects, simplifying the process for existing software using the .NET platform. Smalltalk has been used extensively for simulations, neural networks, machine learning, and genetic algorithms.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
Amazon SageMaker AI is a cloud-based machine-learning platform that allows the creation, training, and deployment by developers of machine-learning (ML) models on the cloud. [1] It can be used to deploy ML models on embedded systems and edge-devices. [2] [3] The platform was launched in November 2017. [4]
TensorFlow serves as a core platform and library for machine learning. TensorFlow's APIs use Keras to allow users to make their own machine-learning models. [33] [43] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving. [44]
General purpose AI; human performance modeling; learning (including explanation-based learning) John E. Laird, Clare Bates Congdon, Mazin Assanie, Nate Derbinsky and Joseph Xu; Division of Computer Science and Engineering, University of Michigan, Ann Arbor, Michigan, USA BSD Soar 1 to 5 in Lisp; Soar 6 in C; Java, C++, TCL Cross-platform
ML.NET is a free software machine learning library for the C# and F# programming languages. [4] [5] [6] It also supports Python models when used together with NimbusML.The preview release of ML.NET included transforms for feature engineering like n-gram creation, and learners to handle binary classification, multi-class classification, and regression tasks. [7]
KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.
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