Using ML.NET to Build Machine Learning Models

INTERACTIVE COURSE

Using ML.NET to Build Machine Learning Models

Intermediate

57 Lessons

40h

Certificate of Completion

AI Explanations

AI Explanations

Using ML.NET to Build Machine Learning Models

1 Project

45 Playgrounds

8 Quizzes

33 Illustrations

Takeaway Skills

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

Course Overview

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 task...Show More

Course Content

1

Introduction to ML.NET

Getting Started

ML.NET Fundamentals

Building Our First Machine Learning Model

ML.NET Project Structure Quiz Yourself on ML.NET Fundamentals Challenge: Adding Fields to a Machine Learning Model Solution Review: Adding Fields to a Machine Learning Model

2

Machine Learning Fundamentals

Training a Machine Learning Model Categories and Tasks of Machine Learning Supervised Learning Unsupervised Learning Reinforcement Learning Quiz Yourself on Machine Learning Fundamentals

3

Selecting a Problem for Machine Learning

Choosing a Task for Machine Learning Evaluating Model Accuracy Using Built-In Supervised Learning Tasks Using Built-In Unsupervised Learning Tasks Quiz Yourself on Selecting a Problem for Machine Learning Challenge: Improving Model Accuracy Solution Review: Improving Model Accuracy

4

Built-In Supervised Learning Tasks in ML.NET

Binary Classification Multiclass Classification Regression Recommendation Forecasting Ranking Quiz Yourself on Supervised Learning Challenge: Performing a Multiclass Classification Solution Review: Performing a Multiclass Classification

5

Built-In Unsupervised Learning Tasks in ML.NET

Anomaly Detection Clustering Quiz Yourself on Unsupervised Learning Challenge: Analyzing Clustered Data Solution Review: Analyzing Clustered Data

6

Deep Learning and Neural Networks

7 Lessons

7

Automating Machine Learning Tasks with AutoML

7 Lessons

8

Saving and Consuming Machine Learning Models

6 Lessons

Building an Image Analysis Application

Project

9

Wrapping Up

1 Lesson

10

Appendix

2 Lessons

COURSE AUTHOR

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