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OpenML: [494] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [495] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
One application of machine learning is to perform regression from training data to build a correlation. In this example, deep learning generates a model from training data that is generated with the function (). An artificial neural network with three layers is used for this example. The first layer is linear, the second layer has a ...
DVC is designed to incorporate the best practices of software development [10] into Machine Learning workflows. [11] It does this by extending the traditional software tool Git by cloud storages for datasets and Machine Learning models. [12] Specifically, DVC makes Machine Learning operations:
LightGBM, short for Light Gradient-Boosting Machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft. [ 4 ] [ 5 ] It is based on decision tree algorithms and used for ranking , classification and other machine learning tasks.
The above example demonstrate the simplicity behind the API design, which makes it similar to popular Python based machine learning kit (scikit-learn). Our objective is to simplify for the user the API and the main machine learning functions such as Classify and Predict.
Torch is an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua. [3] It provides LuaJIT interfaces to deep learning algorithms implemented in C. It was created by the Idiap Research Institute at EPFL. Torch development moved in 2017 to PyTorch, a port of the library to Python. [4] [5] [6]
Flux is an open-source machine-learning software library and ecosystem written in Julia. [1] [6] Its current stable release is v0.15.0 [4] .It has a layer-stacking-based interface for simpler models, and has a strong support on interoperability with other Julia packages instead of a monolithic design. [7]
Cirq was developed by the Google AI Quantum Team, and the public alpha was announced at the International Workshop on Quantum Software and Quantum Machine Learning on July 18, 2018. [2] A demo by QC Ware showed an implementation of QAOA solving an example of the maximum cut problem being solved on a Cirq simulator.