Master Machine Learning Definitions and Concepts
Machine learning feels overwhelming.
There are so many specialty terms and assumed prior knowledge.
You need to start at the beginning with a well considered definition of machine learning, the relevant concepts, terms, problem classes and algorithm types.
You need a map when starting your machine learning journey.
The Machine Learning Foundations guide is the map you need.
It is a 28-page PDF guide that carefully defines machine learning, the concepts related to data, modeling and learning, and presents taxonomies of problems and algorithms.
After completing this guide you will know what machine learning is all about and be able to explain it to friends and colleagues.
Convinced? Jump straight to the description.
What is Machine Learning?
The field of machine learning can be confusing.
There are so many algorithms and problems. Terms that are thrown around and you are expected to know what they mean and where they fit in.
You may turn to books or courses, but even they assume you know your way around data and how the field of machine learning fits in.
Lay Of The Land
You need to know the lay of the land before diving into the field.
You need to start out with the definition of machine learning. A definition that is clear and personal to you that you can use whenever you are asked.
You need to know the key concepts and definitions used in the field of machine learning when talking about data, learning and modeling. You need to know about the common classes of algorithms and problems from a high-level, as well as some specific examples of each class.
Finally, and perhaps most importantly, you need to know how the field of machine learning relates to other fields like artificial intelligence.
Just The Foundations
Machine Learning Foundations is the guide you need, the map you can follow at the start of your machine learning journey.
In this guide you will learn what machine learning is as well as the high-level concepts you need to know to get started in the field.
There are some concepts that once you are aware of will provide a solid foundation for your journey through the field of machine learning. This guide is intended to point out those concepts to you including key definitions, types of problems and classes of algorithm.
Guide Overview
This self-study guide is broken down into 5 parts:
- What is machine learning
- What are the key concepts an definitions in machine learning
- What problems can machine learning address
- What methods does machine learning provide
- What other fields are related to machine learning
This Guide Is For You!
The Machine Learning Foundations guide will lay the foundations you need.
After completing this guide you will have discovered…
- …what machine learning is and the confidence to explain it to friends and colleagues
- …the key concepts related to data, learning and modeling
- …the classes of machine learning problems and examples for each
- …a taxonomy for machine learning algorithms and examples for each
- …the parent and sibling fields of study that machine learning is related
About the Author
Who is behind this?
Hey, I’m Jason Brownlee, a father, husband, developer and author. I have written books on artificial intelligence algorithms and I have a Masters and a PhD in Artificial Intelligence.
I started out as a programmer interested in machine learning and designed and completed small projects to teach myself about the field. This lead down a path of quitting my job, studying as an AI researcher and eventually surfacing back into industry as a programmer again.
I now work in that perfect mix of developing scientific software for real users with actual problems.
I live in Melbourne, Australia and will happily talk machine learning all day long.
Download the Guide Now
This 28-page PDF guide includes:
- 5 authoritative definitions of machine learning
- a glossary of 18 machine learning terms on data, learning and modeling
- 10 examples of machine learning problems
- 4 classes of machine learning problem
- taxonomy of 12 machine learning algorithm types
- 3 foundation fields and 3 progenitor fields of study related to machine learning
Buy Now For $5
Below is an overview of the Machine Learning Foundations guide including a breakdown of the definitions, algorithms and problems that are described.
Overview of the Machine Learning Foundations guide.
Questions
What if I hate the guide?
If you really hate the guide, then I don’t want your money. Just reply to your purchase receipt email within 30 days and I will issue you a refund.
Where can I learn more about you?
I have tons of blog posts on MachineLearningMastery.com covering machine learning and the small projects methodology. Read a few and learn more about my teaching and writing style.
I have another question.
If you have any other questions, please contact me and I will do my best to answer them.