Are you a .NET developer? Would you like to bring machine learning into your applications?
Microsoft recently introduced ML.NET there own machine learning framework especially for .NET developers and C# developers.
What's ML.NET?
ML.NET is a free, open source, and cross platform machine learning framework for the .NET developer platform.
It allows you to train, build, and ship custom machine learning models using C# or F# for a variety of ML scenarios.
It includes features like automated machine learning (AutoML) and tools like ML.NET CLI and ML.NET Model Builder, which make integrating machine learning into your applications even easier.
For more examples of what you can do with ML.NET, Check out our GitHub samples repo
ML.NET Series
In this series, you'll learn
- The concept of Machine Learning?
- What you can do with Machine Learning?
- What ML.NET? What you can do with the Framework?
- How you can get started with ML.NET on Windows, Mac, and Linux using ML.NET Model Builder, ML.NET CLI or code-first using ML.NET API.
- How to build an ML model for sentiment analysis of customer reviews using a binary classification algorithm.
- How to classify incoming GitHub issues into one of the many tags (labels) using a multi-class classification algorithm.
- How to predict taxi fares based on distance traveled, trip time, etc. using a regression algorithm.
- How to recommend movies for users using collaborative filtering based recommendation approach.
- How to build an Image Classification model to classify flowers.
This series is divided into 7 main sessions
- ML.NET - Machine Learning Introduction
- Getting started with ML.NET
- Build a ML model for Sentiment Analysis
- Build a ML model for GitHub Issue classification
- Build a ML model for predicting taxi fares
- Build a ML model for Movie Recommendation
- Deep learning with ML.NET
Continue Learning
