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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 ...
This is a list of free and open-source software (FOSS) packages, computer software licensed under free software licenses and open-source licenses.Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. [1]
[13] [14] All CS50x course materials are free and there is no fee to complete the course, though various verified certificates are available for a fee. [15] As of 2024, CS50x teaches the languages C, Python, SQL, HTML, CSS, and JavaScript. It also teaches fundamental computer science concepts including data structures and the Flask framework. [13]
Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [38] [39] [40] [41]
A certification is a third-party attestation of an individual's level of knowledge or proficiency in a certain industry or profession. They are granted by authorities in the field, such as professional societies and universities, or by private certificate-granting agencies.
SageMath - a system for algebra and geometry experimentation via Python. Scilab - free open-source software for numerical computation and simulation similar to MATLAB/Simulink. Sim4Life.lite - online version of Sim4Life that is free-of-charge for students for team-learning and online collaboration with classmates and teachers on limited size ...
Cost-sensitive machine learning optimizes models based on the specific consequences of misclassifications, making it a valuable tool in various applications. It is especially useful in problems with a high imbalance in class distribution and a high imbalance in associated costs
PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo, a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and inference performance across major cloud platforms.
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