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ML.NET is a free software machine learning … ML.NET is a free software machine learning library for the C# and F# programming languages. 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. Additional ML tasks like anomaly detection and recommendation systems have since been added, and other approaches like deep learning will be included in future versions.rning will be included in future versions.
, ML.NET — бесплатная открытая библиотека со … ML.NET — бесплатная открытая библиотека со средствами машинного обучения для языков программирования C# и F#. Она также поддерживает модели на Python при использовании совместно с NimbusML. Предварительный выпуск ML.NET включал в себя решения для конструирования признаков (например, создания N-грамм), двоичной и мультиклассовой классификаций, регрессионного анализа. Позже были добавлены дополнительные задачи машинного обучения: выявление аномалий и рекомендательные системы. Глубокое обучение и прочие подходы ожидаются в предстоящих версиях.е подходы ожидаются в предстоящих версиях.
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ML.NET — бесплатная открытая библиотека со … ML.NET — бесплатная открытая библиотека со средствами машинного обучения для языков программирования C# и F#. Она также поддерживает модели на Python при использовании совместно с NimbusML. Предварительный выпуск ML.NET включал в себя решения для конструирования признаков (например, создания N-грамм), двоичной и мультиклассовой классификаций, регрессионного анализа. Позже были добавлены дополнительные задачи машинного обучения: выявление аномалий и рекомендательные системы. Глубокое обучение и прочие подходы ожидаются в предстоящих версиях.е подходы ожидаются в предстоящих версиях.
, ML.NET is a free software machine learning … ML.NET is a free software machine learning library for the C# and F# programming languages. 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. Additional ML tasks like anomaly detection and recommendation systems have since been added, and other approaches like deep learning will be included in future versions.rning will be included in future versions.
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