Skip to main content

ML.NET 1.0 RC Announced. What does it mean?

Microsoft has already announced a new the ML.NET 1.0 RC (Release Candidate) (version 1.0.0-preview). This is going to be the last version before the final ML.NET 1.0 in Q2 of 2019. It means soon we will be able to use machine learning with C# using a stable version of the library.
It seems that in the 95% of the functionality in RC is going to be a part of the stable 1.0 version. Nevertheless, some of the packages will remain in the review even after release.
These packages are:
  • TensorFlow components
  • Onnx components
  • TimeSeries components
  • Recommendadtions components
The full list of the preview packages here.

In this release (ML.NET 1.0 RC) Microsoft has initially concluded main API changes and for the next sprint, they are planning to focusing on documentation and samples improvements and also addressing major critical issues if needed.

I want to believe that their goal is to avoid any new breaking changes moving forward. And it all good news for those, who wanted to start use machine learning without changing their favorite language. Based on the list of changes now is a good time to start learning and preparing integrations.

Also in RC release were fixed problems with the use of TensorFlow models, that were introduced in version 0.11. You can check out additional release notes for 1.0 RC here.
Other breaking changes can be found here.

Get ready for ML.NET 1.0 before it releases! Next resources will be useful for going further:

Comments

Popular posts from this blog

Caching strategies

One of the easiest and most popular ways to increase system performance is to use caching. When we introduce caching, we automatically duplicate our data. It's very important to keep your cache and data source in sync (more or less, depends on the requirements of your system) whenever changes occur in the system.
In this article, we will go through the most common cache synchronization strategies, their advantages, and disadvantages, and also popular use cases.

How to Build TypeScript App and Deploy it on GitHub Pages

Quick Summary In this post, I will show you how to easily build and deploy a simple TicksToDate time web app like this: https://zubialevich.github.io/ticks-to-datetime.

Classify BBC news headlines with Microsoft ML.NET

This sample tutorial illustrates using ML.NET to create a multiclass classifier via a .NET Core console application using C# in Visual Studio 2017.

Just another way of fixing bugs

Every developer has to manage with bugs. We have to deal with this because no one is able to write code without errors. Requirements are always changing, systems becoming more complex with time and in such situations, it's hard to not make mistakes.
But how to avoid repetition of the same bugs when you edit a code? There's a good solution that will also save you some time while debugging the reasons of bugs.