Using ML.NET to Build Machine Learning Models
Delve into ML.NET to build and train models for various machine learning tasks. Explore key features, advanced capabilities like deep learning, and integration with TensorFlow.
57 Lessons
40h
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In this course, you will learn how to use ML.NET, which is a tool based on .NET architecture. It consists of a library and command line utility used for building machine learning models. It is so convenient to work with that a developer having little or no background in machine learning and data science can use it to build complex machine learning models.
You will start with an overview of the key ML.NET features and the fundamentals of machine learning. Then, you will go through all types of built-in tasks supported by ML.NET, followed by more advanced ML.NET capabilities, such as deep learning and interoperability with external tools, such as TensorFlow.
By the end of the course, you will be able to use ML.NET to build and train models capable of performing a wide range of machine learning tasks. You will be able to use all the key features of ML.NET and fully integrate it into your apps.
In this course, you will learn how to use ML.NET, which is a tool based on .NET architecture. It consists of a library and comma...Show More
WHAT YOU'LL LEARN
An understanding of machine learning fundamentals
The ability to use ML.NET to perform a wide range of machine learning tasks
In-depth knowledge of supervised and unsupervised machine learning
Familiarity with deep learning and its implementation using ML.NET
Hands-on experience of AutoML and the automatic model building process
An understanding of machine learning fundamentals
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Learning Roadmap
Certificate of Completion
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