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End to End Machine Learning Pipeline Tutorial

spandan-madan.github.io

1–10 of 25 posts

Re: End to End Machine Learning Pipeline Tutorial

#2
Reading articles like this written by people who want to share their fabulous domain knowledge for free of charge really is the reason why I read Hacker News. Thank you, i hope i will have the time to read through it all with thought and later hopefully utilize it with my own projects.

Re: End to End Machine Learning Pipeline Tutorial

#3
post #2

Reading articles like this written by people who want to share their fabulous domain knowledge for free of charge really is the reason why I read Hacker News. Thank you, i hope i will have the time to read through it all with thought and later hopefully utilize it with my own projects.

And people like you who take time out to read and learn is exactly the reason why people like me write such articles! Absolutely thrilled that people liked it and that I will be contributing in people learning this beautiful field of science I do research in :)

Re: End to End Machine Learning Pipeline Tutorial

#5
Great write-up. Especially the fact that half of it was about finding cleaning and structuring data! You can tell someone isn't applying ML if they aren't spending most of their time getting their data organized. It's the "sharpening the axe" part of the hour Lincoln describes.

For example, they never introduce you to how you can run the same algorithm on your own dataset

I actually think the tensorflow tutorial on CNNs actually runs through training and classification on your own set with inception pretty well.

You mention you're a CV student. Any particular area of focus?

Re: End to End Machine Learning Pipeline Tutorial

#7
These are the tutorials that depict the reality of a machine learning career. Everyone broadly understands that data preparation is the key, but few realize what that involves. Half of this tutorial is just about getting and prepping data for training. Kudos!

Re: End to End Machine Learning Pipeline Tutorial

#10
post #2

Reading articles like this written by people who want to share their fabulous domain knowledge for free of charge really is the reason why I read Hacker News. Thank you, i hope i will have the time to read through it all with thought and later hopefully utilize it with my own projects.

And people like you who take time out to read and learn is exactly the reason why people like me write such articles! Absolutely thrilled that people liked it and that I will be contributing in people learning this beautiful field of science I do research in :)

Respect!
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