Educating yourself on machine learning is a challenging preposition. There is so much content online that it’s easy to get fooled into reading an article that is beyond capabilities. Unfortunately, in many cases, reading and rereading this sort of content is often the only way to crack that nut open. But recently I’ve found some great resources that should hopefully be able to help the uninitiated into getting a foothold into this popular segment of IT.
Unfortunately, most of the online content skips right past the basic minimum knowledge required to take the plunge into the technology. So I did some research to find a good definition that did not require prior knowledge to answer that most basic question.
What is Machine Learning?
I found the best answer on SAS’ own website.
Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.
Below are the best resources I’ve found so far to get a good grasp of machine learning at its basic form.
- ML@B – Crash Course Series
- Machine Learning: An In-Depth Guide
- What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning?
- Deep Learning Tutorial
- Neural Networks and Deep Learning
- The 10 Algorithms Machine Learning Engineers Need to Know
- Top 10 Quora Machine Learning Writers and Their Best Advice