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 ...
He joined Cogent Labs, a Japanese Deep Learning/AI company, in 2017. [4] He is a Machine Learning Engineering Manager at Mercari, Inc. [5] Cournapeau has also been involved in the development of other central numerical Python libraries: NumPy and SciPy. [6] [7]
JAX is a machine learning framework for transforming numerical functions. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).
You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.
scikit-learn, an open source machine learning library for Python; Orange, a free data mining software suite, module Orange.ensemble; Weka is a machine learning set of tools that offers variate implementations of boosting algorithms like AdaBoost and LogitBoost
Google JAX is a machine learning framework for transforming numerical functions. [ 71 ] [ 72 ] [ 73 ] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and TensorFlow's XLA (Accelerated Linear Algebra).
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]
Waikato Environment for Knowledge Analysis (Weka) is a collection of machine learning and data analysis free software licensed under the GNU General Public License. It was developed at the University of Waikato, New Zealand and is the companion software to the book "Data Mining: Practical Machine Learning Tools and Techniques". [1]