Machine learning is arguably the most popular starting point for anyone looking to get into data science, and where many organizations start to implement AI into their practice. With AI becoming commonplace in much of the world, even the term “machine learning” itself is starting to become common knowledge.

It’s difficult to say where one should start their machine learning journey. What coding language do you want to use? What tools, platforms, and libraries to work with? What problems do you need to look out for and to avoid? Which machine learning tutorial is right for you?

What about those who already have machine learning experience? How up-to-date are your core mathematical skills? Have you tried any new frameworks out, or are you still relying on the ones you used five years ago? When was the last time you checked out a new machine learning tutorial?

These written machine learning tutorials and videos from past ODSC conferences will hopefully be able to address those questions. Covering from the bare basics with R and Python to avoiding the black box problem, these ODSC resources will help those new to data science get started with machine learning, and already-established pros revisit their toolkit.

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