Curriculum

  1. 1

    Book Preview

    1. Ultimate Machine Learning with ML.NET Free preview
  2. 2

    Introduction

    1. (Included in full purchase)
  3. 3

    Chapter 1 : Introduction to ML.NET

    1. (Included in full purchase)
  4. 4

    Chapter 2 : Installing and Configuring ML.NET

    1. (Included in full purchase)
  5. 5

    Chapter 3 : ML.NET Model Builder and CLI

    1. (Included in full purchase)
  6. 6

    Chapter 4 : Collecting and Preparing Data for ML.NET

    1. (Included in full purchase)
  7. 7

    Chapter 5 : Machine Learning Tasks in ML.NET

    1. (Included in full purchase)
  8. 8

    Chapter 6 : Choosing and Tuning Machine Learning Algorithms in ML.NET

    1. (Included in full purchase)
  9. 9

    Chapter 7 : Inspecting and Interpreting ML.NET Models

    1. (Included in full purchase)
  10. 10

    Chapter 8 : Saving and Loading Models in ML.Net

    1. (Included in full purchase)
  11. 11

    Chapter 9 : Optimizing ML.NET Models for Accuracy

    1. (Included in full purchase)
  12. 12

    Chapter 10 : Deploying ML.NET Models with Azure Functions and Web API

    1. (Included in full purchase)
  13. 13

    INDEX

    1. (Included in full purchase)

About the course

Dive into the world of machine learning for data-driven insights and seamless integration in .NET applications with the Ultimate Machine Learning with ML.NET. The book begins with foundations of ML.NET and seamlessly transitions into practical guidance on installing and configuring it using essential tools like Model Builder and the command-line interface. Next, it dives into the heart of machine learning tasks using ML.NET, exploring classification, regression, and clustering with its versatile functionalities. It will delve deep into the process of selecting and fine-tuning algorithms to achieve optimal performance and accuracy. You will gain valuable insights into inspecting and interpreting ML.NET models, ensuring they meet your expectations and deliver reliable results. It will teach you efficient methods for saving, loading, and sharing your models across projects, facilitating seamless collaboration and reuse. The final section of the book covers advanced techniques for optimizing model accuracy and refining performance. You will be able to deploy your ML.NET models using Azure Functions and Web API, empowering you to integrate machine learning solutions seamlessly into real-world applications.

About the Author

Kalicharan Mahasivabhattu is a seasoned industry expert with over 21 years of experience working with leading global organizations primarily in oil and gas and healthcare. As a Certified Artificial Intelligence and Machine Learning Specialist, he has earned the moniker Serial Innovator for his ground-breaking ideas in deep learning, augmented reality, chatbots, and computer vision, all of which have garnered support from the innovation council. Kali's dedication to advancing the field extends to his engaging podcast, Talking AWS for Data Science, where he shares insights and discusses cutting-edge developments.