ML.NET, Microsoft’s open source machine learning framework, has been updated to version 1.2. Here’s a quick rundown of the updates. Read the article on Visual Studio Magazine to find out more.

  • General availability of TimeSeries support for forecasting and anomaly detection:
  • General availability of ML.NET packages to use TensorFlow and ONNX models:
  • Easily integrate ML.NET models in web or serverless apps with Microsoft.Extensions.ML integration package (preview):
  • ML.NET CLI updated to 0.14 (preview):
  • Model Builder updates:
    • Expanding support to .txt files and more delimiters for values

    • No limits on training data size

    • Smart defaults for training time for large datasets

    • Improved model consumption experience

Along the lines of a recent post about companies that still run SQL 2008, here’s a thread from Slashdot (!) about how the quest for “latest and greatest” often over complicates enterprise tech.

“For better or worse, the world runs on Excel, Java 8, and Sharepoint, and I think it’s important for us as technology professionals to remember and be empathetic of that.”

Here’s a question for the ages and the wise old sages.

Although there are lots of similarities across Software Development and Data Science , they also have three main differences: processes, tooling and behavior. Find out. In my previous article , I talked about model governance and holistic model management. I received great response, along with some questions about the […]

This week Five Things sits down with Noelle LaCharite from the Microsoft Cognitive Services team to learn how machines can translate language, perform search on unstructured data, converse like humans and more.

Best of all, you can add these cutting edge features to your applications right away; no degree in multi-dimensional calculus required.

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