Using ML.NET to Build Machine Learning Models for AI Solutions.png

mlnet.tar.gz

Command Line

Model Execution

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.

Using ML.NET to Build Machine Learning Models

Binary classification requires the `--binary` parameter to be set to `true`, while multiclass classification has it set to `false`.

Binary classification requires the `--multiclass` parameter to be set to `false`, while multiclass classification has it set to `true`.

The command is identical and the classification type is determined by the number of distinct label values.

The command is identical, but for binary classification, the label values must be integers of either `1` or `0`.

What is the difference between the ML.NET commands executed for binary classification and multiclass classification?

What is the difference between the ML.NET commands executed for binary classification and multiclass classification?

The `label` column isn’t applicable to recommendations.

To store the unique identifier of an item

What is the `label` column used for in the recommendations ML task? 

What is the <code>label</code> column used for in the recommendations ML task?

Regression doesn't rely on time series, while forecasting does.

Forecasting doesn't rely on time series, while regression does.

Regression can only predict a categorical label value, while forecasting can predict a scalar label value.

Regression only works with integers, while forecasting can work with fractional numbers.

What is the key difference between regression and forecasting?

What is the key difference between regression and forecasting?

If you wanted to assess the performance of your web pages against specific search keywords, which ML task would you choose?

If you wanted to assess the performance of your web pages against specific search keywords, which ML task would you choose?

Let's assume you have an online shop. You have many items of different categories with different prices. A new item comes in that you haven't yet determined the price of. What ML task would you use to help come up with the retail price for the new item?

Let’s assume you have an online shop. You have many items of different categories with different prices. A new item comes in that you haven’t yet determined the price of. What ML task would you use to help come up with the retail price for the new item?

Quiz

Quiz

Test your knowledge of supervised learning tasks available in ML.NET.

Introduction to ML.NET

Machine Learning Fundamentals

Selecting a Problem for Machine Learning

Built-In Supervised Learning Tasks in ML.NET

Built-In Unsupervised Learning Tasks in ML.NET

Deep Learning and Neural Networks

Automating Machine Learning Tasks with AutoML

Saving and Consuming Machine Learning Models

Building an Image Analysis Application

Wrapping Up

Appendix

Quiz Yourself on Supervised Learning