There has been a lot of buzz in the past few days on this recent crash course in machine learning by Google. You don't have to be a fortune teller to guess that it's gonna use the TensorFlow API. :)
So, are there any prerequisites? If so, what are they?
Well, yes they are. At a basic minimum, Google says that you should master algebra and be proficient in basic programming. Even though they're trying to cut it to its most naked form, I'd say that you should probably know more math than just algebra and to be at least at an intermediate level of programming.
They do break it down in subtopics when it comes to the prerequisites though. So, you'll be wanting to known linear algebra, trigonometry, statistics, calculus; and when it comes to programming, you should be at least familiar with a couple of libraries in Python, such as numpy, pandas, and matplotlib.
So, they recommend getting through all the prereqs before getting into the course. Then, during the course, you will learn about:
- introductory TensorFlow
- generalization, validation, representation
- regularization
- logistic regression
- neural networks
- and much more.
They also cover (in short) some real world examples like machine learning in cancer prediction as well as a problem of debugging related to literature.
I'd say that if you're good to go with the pre-requisites and you're eager to learn machine learning, this course is a great start, especially since it comes from Google. And it's free! So, head over to the link below and begin working through it if you think this is for you:
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Cristi Vlad Self-Experimenter and Author