putnam

Another resource - https://sigopt.com/, in the vein of Whetlab.

e.g. For NLP:

* https://aws.amazon.com/blogs/ai/fast-cnn-tuning-with-aws-gpu...

Disclaimer: they did share free trials with some of our students.

Coming from a signal processing background, this is interesting. Would your company be interested in doing a newsletter with https://enterprisedeeplearning.github.io?

Edit: softened the sales pitch

Do you think the management who made this decision would pay for this service in an industry-specific but company non-specific form on a subscription basis?

To the now 9 people who said they want this and the rest like me who didn't enter your information - do you want industry-specific (but of course company-agnostic) code examples or are you amply satisfied with audio walkthroughs, as in once or twice a week you get a free podcast, and your $11/month could pay for, e.g., transcripts of the conversations?

So, there's a lot of material out there but it's disjointed. If you get annoyed implementing your own neural net with only Python + Numpy, you might try some more complex examples just to immediately point at them and say "I ran this" and "It did that". (The article uses neural networks so I'm addressing that here even though your question and the article title use the much broader 'ML'.)

1) Brandon Rohrer, now Data Scientist at Facebook, has a few great talks, including one on Bayes' Theorem/Bayesian Inference - https://m.youtube.com/playlist?list=PLVZqlMpoM6kbaeySxhdtgQP...

2) When asking future data scientists what tutorials for ML/NNs they like, they have usually found http://machinelearningmastery.com/ through Google and swear by it.

3) Josh Gordon, Developer Advocate at Google, has some simple ML/DL videos up in a 'Recipes' playlist: https://m.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFY...

If you want to just step through other people's code, you can do that too. Disclaimer: I put the below list together and it's not for ML broadly but for DL. That said if you want to run some examples fast and see the output, a number of folks have made that work for you -

I for one was floored to find great iOS examples (admittedly now deprecated for iOS 11). But If you have an iPhone with Metal (5s and up) Matthijs Hollemans - who wrote the iOS Apprentice at Ray Wenderlich - has Inception, YOLO, and MobileNets pre-trained and ready to go using Xcode, and it's fun to watch them work on your phone - https://medium.com/@SamPutnam/deep-learning-download-and-run...

Thank you

Yes

So Accenture does due diligence on the expected ROI from the product?

What if you're offering a SaaS product that no one there (but everyone on HN) gets - Is it possible to be both Accenture (review and craft a deal and explain the benefit to the business really well) and also be the software-as-a-service if the client has never bought anything like this before?

Context: I am trying to sell DL consulting/productized models but enterprises either say 'we don't really do that' or 'we do that but we don't work with consultants'.

Thanks for asking. Would like this too.

I think computing optical flow remains a major time bottleneck. Any attempt at temporal coherence would be great, and I'm sure there is some attempt on Messenger, but it really only works well for the last style transfer filter, all the way to the right in the app, and that one only really looks great in well lit scenes. Also, the phone seems to heat up a lot.