Andrew Ng&#x27;s Coursera ML course is supposed to be pretty accessible. I&#x27;ve also heard good things about Machine Learning for Hackers (<a href="http:&#x2F;&#x2F;www.amazon.com&#x2F;Machine-Learning-Hackers-Drew-Conway&#x2F;dp&#x2F;1449303714" rel="nofollow">http:&#x2F;&#x2F;www.amazon.com&#x2F;Machine-Learning-Hackers-Drew-Conway&#x2F;d...</a>).<p>Ultimately, ML is a mathematical discipline. You can ask for a gentle approach that gets you to the foot of the mountain, but &quot;if you want to learn about nature, to appreciate nature, it is necessary to understand the language that she speaks in.&quot; If you want to be more than an amateur, there&#x27;s not much substitute for getting comfortable with math at the level of, say, Kevin Murphy&#x27;s book.<p>The good news is that the required math is fairly elementary - calculus, linear algebra, probability and statistics, all freshmen or maybe sophomore-level topics - so it shouldn&#x27;t be beyond reach of a motivated developer able to set aside some time to learn. MOOCs and organizing study groups with friends&#x2F;co-workers can help a lot here as well.