
Show HN: Deep Learning in TensorFlow – The Roadmap for Study and Learning - irsina
https://github.com/astorfi/TensorFlow-Roadmap
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m0zg
Some well considered advice: drop TensorFlow and go with PyTorch. Spend your
effort where it will make a difference: on deep learning, rather than on
fighting with the framework.

People just keep using TF because it was the first full-fledged Python
framework for this, not because it has any technical merit anymore. In PyTorch
you will make twice as much progress in half the time.

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jorgemf
Is there any way to use a pytorch model in Mobile and in a website without a
server API? For me 5hose are two good reasons to keep using TensorFlow.

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m0zg
[https://caffe2.ai/docs/AI-Camera-demo-
android.html](https://caffe2.ai/docs/AI-Camera-demo-android.html)?

Not something I've used myself, but supposedly yes.

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jorgemf
Thanks. I always forgot about caffe2 when talking about pytorch. I couldn't
anything for JavaScript and mobile seems not as good supported as TF but for
sure they will improve.

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m0zg
Have you actually used TFLite? It's slow as molasses. Deploying on mobile is a
bit of a shitshow across the board right now, from what I undertand. Not all
models are supported out of the box (especially with ONNX), and the ones that
are supported aren't guaranteed to have acceptable performance with off-the-
shelf frameworks. Documentation is very sparse as well, especially for the
quantized stuff.

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partingshots
Not disparaging the author, good on you for working on building this! I’m sure
you learned a lot from just compiling everything together.

My question is, isn’t everything in this guide pretty much just a straight up
copy of the actual TensorFlow docs/guides? What’s the difference?

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eternal_virgin
It would be great to have some sort of roadmap depending on "what" the user is
trying to do.

i.e. if I was a total noob and I wanted to make an application using AI to
detect if people in the crowd were bored, I would have no idea where to start
without reading/researching for hours online on different fields and models
that work and how they work. It would be neat if there was a tool that just
asked you a few questions, then took that info and gave you a roadmap, i.e.
"Feed Forward Neural Networks, Digit Classification, Image Classification w/
Inception, Object Detection with ResNet + Inception, Optimizing TensorFlow
code for Servers, Deploying TensorFlow with Docker, Protecting Against
Adversarial Input"

This way someone with a time sensitive project doesn't have to learn TF for 6
months before being able to accomplish what they wanted! Just something I
think would be neat and also possible to add to TF World.

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jorgemf
There are not so many type of problems for such a complex tool. Your problem
usually fits in one category among classification, prediction, clustering,
generation or control. Then you have different domains as images, video,
audio, text, etc. With a combination or type of problem and domain you sure
can have a roadmap, but you probably will need to read papers to solve your
problem if it is not something some has done before.

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Aduket
What do you mean by “control”? Like control engineering? How is it used in
control domain, can you explain a bit?

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yeonsh
Thanks for the list.

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mywrathacademia
This guide will be useful.

