
Open-Source Machine Learning Repos to Inspire Your Next Project - onmyway133
https://heartbeat.fritz.ai/25-open-source-machine-learning-repos-to-inspire-your-next-project-3b027a90155
======
akavel
I'm curious why I don't see any projects applying new ML techniques to text
recognition (OCR) in those "advertisements" popping up recently; is this
because:

\- too boring/mundane?

\- "solved problem"/too easy? (then where are the [open source] solutions? is
Tesseract-ocr advanced enough already? what's its status?)

\- too hard? (is Tesseract-ocr using the state-of-the-art techniques?)

------
lelima
Nice wrap up of ideas, but I wonder why people don't get attention on ML
project with structured data, which is the most common btw.

I know that predicting sales is not as fun as make Horse a Zebra but I think
they're underrated.

pd: If you have nice ML repos with structured data I'll appreciated :)

~~~
jamesonthecrow
Great point! I haven’t tried it yet, but Sales Force just opensourced
Transmogrifai, a platform that does just this:

[https://engineering.salesforce.com/open-sourcing-
transmogrif...](https://engineering.salesforce.com/open-sourcing-
transmogrifai-4e5d0e098da2?gi=f2653bb323b3)

------
montenegrohugo
Thanks for the list, I've been thinking of contributing to an OS project
recently. These all look extremely interesting, hopefully I can be helpful

------
cpcat
Any of these work completely in iOS? I'm new in the field and want to embed
everything in mobile

~~~
jamesonthecrow
Core ML is going to be your best bet. Most training is still done server side
using frameworks like TensorFlow, Keras, and PyTorch. Once you've trained your
model, you can convert it to Core ML with coremltools or export it to Core ML
directly if the platform supports it.

Apple has a couple tools, Turi Create and Create ML, to train ML models
specifically for mobile use, but their not nearly as fully featured or widely
used.

If you're interested specifically in mobile ML, check out
[https://heartbeat.fritz.ai](https://heartbeat.fritz.ai). We've got a bunch of
resources for mobile machine learning. If you're looking for ready-to-use
models or tools to manage them in your app, check out Fritz
([https://fritz.ai](https://fritz.ai)). Disclaimer, I'm a founder at Fritz
which sponsors Heartbeat. Happy to answer any questions!

~~~
cpcat
I'm not sure yet whether i want to do the training on mobile, but i want to
try both before i decide so thanks for the resources i'll dig into them. One
important question is, are there tools to decrease the size of a model so it'd
better fit on mobile? Or is that part of the training?

