stream:// data science


Introducing the SparkFun Edge

Introducing the SparkFun Edge

March 09, 2019
  188
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.
.NET Blog | Announcing ML.NET 0.11 – Machine Learning for .NET

.NET Blog | Announcing ML.NET 0.11 – Machine Learning for .NET

March 09, 2019
  206
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,
Announcing ML.NET 0.10 – Machine Learning for .NET

Announcing ML.NET 0.10 – Machine Learning for .NET

February 14, 2019
  115
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.
Getting started with FsLab - FsLab

Getting started with FsLab - FsLab

January 30, 2019
  136
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
GitHub: The top 10 programming languages for machine learning

GitHub: The top 10 programming languages for machine learning

January 28, 2019
  154
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.
Announcing ML.NET 0.9 – Machine Learning for .NET

Announcing ML.NET 0.9 – Machine Learning for .NET

January 12, 2019
  135
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.
Machine Learning in NET (ML NET) full tutorial

Machine Learning in NET (ML NET) full tutorial

December 28, 2018
  228
Machine Learning in NET (ML NET) full tutorial
A Year of Q#

A Year of Q#

December 13, 2018
  139
The Quantum Architecture and Computation group launched Q#, our quantum computing programming language, a year ago on December 11th, 2017. Q# 0.1 was the result of a lot of hard work from a small, dedicated team of developers, researchers, and program managers. We had made the decision to build a domain-specific language for quantum computing about six months before we launched, so we were on a very tight schedule. We were lucky to have a great team of people who all pitched in and did what needed to be done so that we could meet our extremely aggressive timetable.
Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI

Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI

December 11, 2018
  149
Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI KDnuggets   Subscribe to KDnuggets News  |       &
Microsoft Puts More Brain-Power Into Machine Learning For Azure Cloud

Microsoft Puts More Brain-Power Into Machine Learning For Azure Cloud

December 10, 2018
  211
Computer brains need models that can be exposed to datasets, trained, tested and enriched over time as they learn what’s right, what’s wrong and ultimately what is altogether culturally and ethically appropriate or not.

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