Basic Econometrics First Before Machine Learning!
Machine learning is an incredibly hot topic and it seems that there are thousands of tutorials available online. My own journey into machine learning was a relatively simple matter as I have been teaching and doing academic research in applied econometrics for over 20 years. Many of the issues I find that beginners in this field face come from a lack of basic knowledge about applied econometrics. Now, I'm not saying that you need to know all of the math and statistics jargon right away, but doing econometrics is a very important first step. What is doing econometrics mean? It means getting some data, running an econometrics model, and interpreting the results.
There are many tutorials on basic econometrics, but one of my favorite online courses is offered by www.burkeyacademy.com. In the top right hand side of the page, there is a link to Statistics/Econometrics, which includes both a basic statistics course and basic econometrics course. The classes on Burkey Academy use the R statistical language, but for those of you who love Python, I would recommend this repository on GitHub.
Personally, I would go through the Burkey Academy materials first to understand the basic statistical concepts, and then look at the Python code. Python is the #1 programming language for machine learning and deep learning, so it's probably a good idea to learn basic Python for data science.
Donald J. Lacombe
Donald Lacombe is an Associate Professor in the School of Financial Planning, Texas Tech University and the Chief Statistical Officer, Quantum Hedonics.