Title: I&#x27;ll spend all my time next week studying machine learning. However, I know that it&#x27;s easy to get lost in overly theoretical material when learning ML.<p>So I&#x27;m interested in some advice on how to best spend my time, given that I&#x27;d like to get as much practical knowledge as possible.<p>Here is the level I&#x27;m at now:<p>I&#x27;m currently halfways though Andrew Ng&#x27;s ML course on Coursera, and will probably finish this within the week. I love the mix of theory an practice this course is based around.<p>I&#x27;ve also done the Udacity - Intro to Machine Learning, but found it too theoretical.<p>I kind of understand the basic principles of linear &amp; logistic regression, cost functions and gradient descent &amp; the normal equation.<p>By the end of the week, I hope to be able to do linear regression using gradient descent on an actual dataset. If so, the week has been very well spent!<p>My preferred language is Python.<p>All tips and suggestions are highly appreciated :)
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