Machine Learning with ML.Net for Absolute Beginners

Use your dotnet skills for building Machine Learning apps using ML.Net

What Will You Learn?

  • Create a Machine Learning app with C#
  • Use TensorFlow or ONNX model with dotnet app
  • Using Machine Learning model in ASP.Net
  • Use AutoML to generate ML dotnet model

Requirements

  • Basic C# development
  • Basic concept of Machine Learning
  • Visual Studio 2019

Who is the target audience?

  • This is for newbies who want to learn Machine Learning
  • Developer who knows C# and want to use those skills for Machine Learning too
  • A person who wants to create a Machine Learning model with C#
  • Developer who want to create Machine Learning

Course Description

Note: This course is designed with ML.Net 1.5.0-preview2

Machine Learning is learning from experience and making predictions based on its experience.

In Machine Learning, we need to create a pipeline, and pass training data based on that Machine will learn how to react on data.

ML.NET gives you the ability to add machine learning to .NET applications.

We are going to use C# throughout this series, but F# also supported by ML.Net.

ML.Net officially publicly announced in Build 2019.

It is a free, open-source, and cross-platform.

It is available on both the dotnet core as well as the dotnet framework.


The course outline includes:

  • Introduction to Machine Learning. And understood how it’s different from Deep Learning and Artificial Intelligence.
  • Learn what is ML.Net and understood the structure of ML.Net SDK.
  • Create a first model for Regression. And perform a prediction on it.
  • Evaluate model and cross-validate with data.
  • Load data from various sources like file, database, and binary.
  • Filter out data from the data view.
  • Export created the model and load saved model for performing further operations.
  • Learn about binary classification and use it for creating a model with different trainers.
  • Perform sentimental analysis on text data to determine user’s intention is positive or negative.
  • Use the Multiclass classification for prediction.
  • Use the TensorFlow model for computer vision to determine which object represent by images.
  • Then we will see examples of using other trainers like Anomaly Detection, Ranking, Forecasting, Clustering, and Recommendation.
  • Perform Transformation on data related to Text, Conversion, Categorical, TimeSeries, etc.
  • Then see how we can perform AutoML using ModelBuilder UI and CLI.
  • Learn what is ONNX, and how we can create and use ONNX models.
  • Then see how we can use models to perform predictions from ASP.Net Core.

About Instructor

Nilay Mehta

Passionate Software Engineer and Instructor

Hey, My name is Nilay Mehta! I am an experienced .Net developer, having the Microsoft certificate of Programming with C#.Net.

I have a Master of Computer Applications and Bachelor of Computer Application degrees. Starting out in the IT industry about 3 years ago. I've worked with a range of development tools from PHP, C#, ASP.NET, and ASP.Net core.

I am a passionate software engineer who loves learning new technologies, and from the past 3 years, I'm enjoying sharing that knowledge through blogs and courses.