stream:// data science


May 04, 2019
  426
The most usual question that I get on the meetups and conferences is “How much math should I know to get into the field?”. This was the question that I asked myself long ago when I started my journey through this universe.
April 26, 2019
  528
ML.NET makes machine learning accessible to the .NET developer community. Up until now, the machine learning space has been dominated by other languages such as Python and C++. With ML.NET, .NET developers get access to a whole host of machine learning techniques for solving various problems. ML.NET makes integrating intelligent systems into an existing codebase …
April 10, 2019
  552
ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS) for .NET developers. Using ML.NET, developers can leverage their existing tools and skillsets to develop and infuse custom AI into their applications by creating custom machine learning models for common scenarios like Sentiment Analysis,
March 09, 2019
  643
For the last month I’ve been carrying around a small square micro-controller board in my laptop bag, and I’ve been dying to tell people more about it. But I haven’t been able to until today. Announced a few minutes ago from the stage of this year’s TensorFlow Dev Summit in Santa Clara, CA, by Pete Warden, part of the TensorFlow Lite team at Google, say “Hello” to the SparkFun Edge.
March 09, 2019
  645
ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS) for .NET developers. Using ML.NET, developers can leverage their existing tools and skillsets to develop and infuse custom AI into their applications by creating custom machine learning models for common scenarios like Sentiment Analysis,
February 14, 2019
  581
ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS) for .NET developers. Using ML.NET, developers can leverage their existing tools and skillsets to develop and infuse custom AI into their applications by creating custom machine learning models. ML.NET allows you to create and use machine learning models targeting common tasks such as classification, regression, clustering, ranking, recommendations and anomaly detection. It also supports the broader open source ecosystem by proving integration with popular deep-learning frameworks like TensorFlow and interoperability through ONNX. Some common use cases of ML.NET are scenarios like Sentiment Analysis, Recommendations, Image Classification, Sales Forecast, etc. Please see our samples for more scenarios.
January 30, 2019
  648
FsLab is a curated collection of open source F# packages for data-science. Together with your editor or Jupyter notebook these packages allow you to rapidly develop scalable, high-performance analytics and visualizations using succinct, type-safe, production-ready code. Download
January 28, 2019
  612
Online code repository GitHub has pulled together the 10 most popular programming languages used for machine learning hosted on its service, and, while Python tops the list, there's a few surprises.
January 12, 2019
  608
ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS) for .NET developers. Using ML.NET, developers can leverage their existing tools and skillsets to develop and infuse custom AI into their applications by creating custom machine learning models.
December 28, 2018
  857
Machine Learning in NET (ML NET) full tutorial

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