Your Applied Machine Learning Process
You know some machine learning algorithms, but you don’t know how to apply machine learning to your own problem domains.
You may have taken a course or read a book and learned about different algorithms. You know what machine learning is all about but you are frustrated because there is no clear and structured way to apply it to your own problem domains.
You are eager to apply the knowledge and algorithms you have learned about, but you need a process. There is a clear and structured process for applying machine learning to new problem domains.
I have created a step-by-step structured process for applying machine learning. It is a 30-page PDF guide called:
The Applied Machine Learning Process
If you want to be able to consistently and effectively tackle new machine learning problems, then this guide is for you!
Convinced? .
You’re Eager to Put Your Skills to Use
You have read a machine learning book, taken a course or similar. You know what machine learning is about in terms of the definitions and core concepts. You have picked up a few algorithms and methods and you want to get to work using them.
You’re main frustration is that…
… you want to know the general process for applying machine learning algorithms
… you are eager to apply machine learning to your own problems
… you are looking for a structured step-by-step to solve problems with machine learning
A Problem You Want to Solve
You have a problem that you want to tackle with machine learning, you just don’t know the best way.
You may want to…
… work on a standard machine learning dataset
… work on a machine learning competition
… address a problem at work and present the results
You need a process you can pick up and apply at the drop of a hat. A process you can customize for your specific use case. And a process you can build upon and extend on your machine learning journey.
The Process No One Talks About
Machine learning books and courses talk about algorithms. It is true that the most interesting part of machine learning is the algorithms. They provide the power for learning how to turn data into decisions.
Nobody seems to talk about the process for systematically applying machine learning.
You don’t need an abstract set of heuristics to follow. You need a concrete plan you can follow to apply any of a suite of algorithms to any classification or regression problem.
The process must be…
… step-by-step so that you know what to do and when to do it.
… explained so you know exactly what to do and why it is important
… concrete so that you can use it on your own problems with the tools and libraries of your choice
Your Step-by-Step Machine Learning Process
I have read and distilled the academic papers and textbooks into a clear and easy to follow process for applying machine learning to problems.
I have refined and simplified the process to its essence over years of working on applied machine learning problems in competitions, for clients and for my own problems.
I’ve used it myself for years to…
… do well in machine learning competitions
… address and present on problems for clients
… teach students how to get the most out of machine learning tools and libraries
Process Overview
The systematic framework is divided into 6 steps:
Problem Definition: Understand and clearly describe the problem that is being solved.
Analyze Data: Understand the information available that will be used to develop a model.
Prepare Data: Discover and expose the structure in the dataset.
Evaluate Algorithms: Develop a test harness and baseline accuracy from which to improve.
Improve Results: Leverage results to develop more accurate models.
Present Results: Describe the problem and solution so that it can be understood by third parties.
The process is a powerful tool for your own machine learning projects because it clarifies what you are trying to do and ensures you capture what you learned and why it matters.
The process is also a powertool for competitions and industry problems because it ensures you make time to get the best result you can and that you make time to effectively communicate your findings.
Below are some tips for getting the most from this process:
Use the process linearly end-to-end on your problem first.
Loop around and revisit steps to improve results or make deeper discoveries.
Use each step as a template to develop your own refined tactics for getting results.
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
You will get a 30ipage PDF guide that includes…
…a 6 part process for applying machine learning
…a blueprint for solving problems now and in the future
…a framework that you can customize and adapt to your needs
…a problem and algorithm agnostic process
Bonus
Project Template and Checklist
Get a bonus 5-page PDF template that includes:
…a summary of the objectives of each step
…a checklist for the whole process
…specific questions for you to answer about your problem at each step
Buy Now For $11Below is an overview of the Applied Machine Learning Process guide that highlights each of the six steps in the process and the specific activities to perform at each step.
Overview of the Applied Machine Learning Process
Frequently Asked 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 this self-study guide. 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.
