Start your machine learning journey

a email from jason@MachineLearningMastery.com

Hey, the way machine learning is taught is crap. It’s backwards.

Books and courses start with the theory and math. If there is any time left at the end, they might touch on how to actually implement or use an algorithm in practice.

Almost no one talks about how to apply machine learning end-to-end to actual problems.

The approach I teach here at Machine Learning Mastery is the other way around. I teach machine learning using a top-down process that focuses on results-first. The result is that you can deliver real value with machine learning a lot sooner which boosts your confidence and skills to continue and take on some of the more challenging material.

With modern tools, it is possible to work through small problems in minutes to hours using complex state-of-the-art algorithms and rigorous validation and statistical techniques, all performed easily and automatically. It is after you’re familiar and confident with the process that I advise that you start looking deeper into the algorithms and theory side of machine learning.

Now, here’s a peek at what is coming up for you in this step-by-step crash course. You’ll discover a self-study roadmap and activities you should be doing. You’ll discover the foundation definitions and concepts in machine learning. You’ll learn about the process of applied machine learning and the template for each step. You’ll learn how to use top tools and libraries to apply machine learning (like Weka, scikit-learn and R). You’ll learn about deep learning and the XGBoost library that is winning competitions. You’ll discover the “small projects” approach to more advanced self-study. You’ll discover why machine learning matters and address your self-limiting beliefs. You will be able to work a machine learning problem end-to-end using a variety of state-of-the-art tools, libraries and algorithms.

And even better, you will have the hunger to dive deeper into the details and the confidence to understand and use what you find.

Excited?

I’ll speak to you soon.

Jason.