Get Started and Make Progress in Machine Learning

 In this post I layout my manifesto for how you can get started and make progress in machine learning.

In this post you will discover what machine learning is, why it matters, how to do it and how to identify and overcome your self-limiting beliefs.

Why Get Started in Machine Learning

I believe machine learning is an important and fascinating field.

• You can make a difference in problem domains that affect a lot of people.
• Machine learning adds more than a new tool to your toolbox, it gives you a superpower.
• There is nothing like it, algorithms that learn from data.
• The time is ripe given computing power, data availability, demand for skills and the growing community

What is Machine Learning

I believe machine learning is a tool required for solving a specific type of problem.

• Some problems are not tractable with hand-crafted programs.
• Machine learning methods are those that automatically create programs from data in service of problems.
• Applied machine learning requires an adjustment in thinking from designing a solution to evaluating candidate solutions.
• It is a field comprised of data, tools and algorithms and only good process can take you from problem to solution.

How to Get Started and Make Progress

I believe machine learning is learned best by doing.

• Use standard datasets and an off-the-shelf tools in projects and deliver a useful predictive model for the data.
• Keep each project small, 5-10 man hours so that you can complete it within a week of nights.
• Study different datasets, algorithms, and tools and study other peoples completed projects.
• Build a portfolio of completed projects that you can build upon and demonstrate your growing capabilities.
• Follow a step-by-step process for working a problem end-to-end and refine that process on each iteration.

But, What If…

I believe you can learn and apply machine learning, right now.

• Stop preparing to study machine learning and start a machine learning project.
• Machine learning is just another technology that you can pick-up and apply to solve complex problems.
• Skills in programming and mathematics can make some tasks easier, but are not required to get started and solve problems.
• Applied machine learning is a meritocracy, where your ability to achieve results matters more than your background.
• It is a job of creativity that is not the exclusive domain of applied mathematicians.

Summary

So what are you waiting for?