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> The obsolete gatekeeping by the AI/ML elites who say "you can't use AI/ML unless you have a PhD/5 years research experience" is one of the things I really hate about the industry.

So what are they hoping to achieve with this course? I'm genuinely asking because part of me wants to take the course, but another part of me feels like what's the point if, even through many additional courses to build up a skill set, Google wouldn't hire you as an ML engineer unless you basically start your career back to a junior engineer but in machine learning at another company.



I have a feeling that they're trying to get people familiar with TensorFlow and thus very compatible with their cloud computing services.


I dunno.. for this level of ml scikit/numpy is way more accessible than tensorflow.


Look at it from an interview perspective. If I ask "are you interested in exploring ML", and you're enthusiastic, my next questions are : What have you done? Have you taken any courses? GitHub? Blog Posts?

If the answer is that you're waiting for a special sign that it's worth doing before making an effort, then that really tells me that your enthusiasm for doing ML is not reality-based. Doing the ML thing is a pretty different mindset from other software jobs.


No but you'll ready yourself for the (geometric) programming of the next twenty years or so.




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