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Machine Learning Crash Course

developers.google.com

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Re: Machine Learning Crash Course

#181

we recommend that students meet the following prerequisites:Mastery of intro-level algebra. You should be comfortable with variables and coefficients, linear equations, graphs of functions, and histograms Any book suggestions to getting up to speed in this area?

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Re: Machine Learning Crash Course

#182

we recommend that students meet the following prerequisites:Mastery of intro-level algebra. You should be comfortable with variables and coefficients, linear equations, graphs of functions, and histograms Any book suggestions to getting up to speed in this area?

If you're looking for books, have a look at Schaum's Outline of Precalculus [0]. Khan Academy [1] is also good and there's this MOOC on coursera called Data Science Math Skills [2].

[0] https://www.amazon.com/Schaums-Outline-Precalculus-3rd-Probl...

[1] https://www.khanacademy.org/math

[2] https://www.coursera.org/learn/datasciencemathskills

Re: Machine Learning Crash Course

#183

This looks like a well put-together course, and a good way to learn TensorFlow. Keras and TensorFlow are top of my list of technologies to explore in the very near future. Is anyone here doing Andrew Ng's Machine Learning course [1]? I'm about half-way through and really enjoying it. I'm particularly appreciating that the programming exercises are done in MatLab/Octave, so I feel that I'm really understanding the fun…

I used to download all ML videos for offline ad hoc watching. But, this crash course videos cannot be downloaded using 'youtube-dl'. Any recommendations?

Re: Machine Learning Crash Course

#184
Cool tutorial, but I'm not entirely sure what makes this ML -- aside from neural nets, this is more or less the material you'd encounter in a basic applied statistics or regression analysis course, minus material on estimating uncertainty, modeling survival or time-series data, and causal inference. I suspect you'd benefit more from a 50 minute tutorial on those than neural nets.

Re: Machine Learning Crash Course

#186

Earlier quoted context omitted.

Khan Academy probably has this covered.

A shame Google doesn’t just link to the Khan Academy course.

not true. they do have khan academy link where applicable. for example for the algebra ones. check below link https://developers.google.com/machine-learning/crash-course/...

Re: Machine Learning Crash Course

#189

Looking through the topics covered, the standard AI-course caveats ( https://news.ycombinator.com/item?id=16247629 ) apply. Yes, AI/ML MOOCs teach the corresponding tools well, and the creation of new tools like Keras make the field much more accessible. 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…

> taking and passing a crash course doesn't mean you'll be an expert in the field (and this applies for most MOOCs, honestly)

You're stating the painfully obvious here. I doubt anyone reading HN is under the impression that they'll be an expert after a single online course.

This is just a marketing stunt by Google to ensure their tooling is the defacto standard for AI/ML so that Google can dominate the AI/ML market they way they dominated Internet Search.

Re: Machine Learning Crash Course

#190

This looks like a well put-together course, and a good way to learn TensorFlow. Keras and TensorFlow are top of my list of technologies to explore in the very near future. Is anyone here doing Andrew Ng's Machine Learning course [1]? I'm about half-way through and really enjoying it. I'm particularly appreciating that the programming exercises are done in MatLab/Octave, so I feel that I'm really understanding the fun…

I used to download all ML videos for offline ad hoc watching. But, this crash course videos cannot be downloaded using 'youtube-dl'. Any recommendations?

Use the time you spend trying to find how to download the videos actually watching them, doing the readings and practising the exercises.
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