jamesonthecrow

6 ms·

1.
Building an on-device face mask detector(heartbeat.fritz.ai)
1 points by jamesonthecrow 6y ago|0 comments
2.
Deep learning has a size problem(heartbeat.fritz.ai)
131 points by jamesonthecrow 7y ago|45 comments
3.
by jamesonthecrow 7y ago
Obviously the big cloud players offer their own APIs and SDKs (for a price), but there are a few other solutions worth looking at. Facebook has open sourced some pre-trained models: https://github.com/facebookresearch/w
4.
On-device training in Core ML 3 and why it matters for developers(heartbeat.fritz.ai)
2 points by jamesonthecrow 7y ago|0 comments
5.
Combining artificial intelligence and augmented reality in mobile apps(heartbeat.fritz.ai)
5 points by jamesonthecrow 7y ago|0 comments
6.
Synthetic data: your data moat is shallower than you think(heartbeat.fritz.ai)
3 points by jamesonthecrow 7y ago|0 comments
7.
Synthetic Data: A bridge over the data moat(heartbeat.fritz.ai)
6 points by jamesonthecrow 7y ago|1 comments
8.
by jamesonthecrow 8y ago
Awesome job! If anyone else is working on a project like this or is interested in learning more about applied machine learning we've got a helpful Slack community over at Heartbeat ( https://bit.ly/heartbeatslack )
9.
Distributing on-device machine learning models with hardware targeting(heartbeat.fritz.ai)
3 points by jamesonthecrow 8y ago|0 comments
10.
Building an iOS app to recognize handwritten digits with Core ML(heartbeat.fritz.ai)
1 points by jamesonthecrow 8y ago|0 comments
11.
Best of Machine Learning in 2018: Reddit Edition(heartbeat.fritz.ai)
5 points by jamesonthecrow 8y ago|0 comments
12.
Creating an extremely tiny, 17 KB style transfer model with just 11,868 weights(heartbeat.fritz.ai)
2 points by jamesonthecrow 8y ago|0 comments
13.
Simplifying user experience with Create ML and on-device text classification(heartbeat.fritz.ai)
1 points by jamesonthecrow 8y ago|0 comments
14.
Streamlining the Reddit app's submission UX with natural language processing(heartbeat.fritz.ai)
2 points by jamesonthecrow 8y ago|0 comments
15.
by jamesonthecrow 8y ago
This looks really neat and it's definitely fun to play around with. I can't resist playing around with tools like this for a few minutes, but I've never really figured out what they're good for. What am I supposed to lea
16.
by jamesonthecrow 8y ago
Regardless of whether or not this would make anyone money, it's a really nice introduction to forecasting time series using LSTMs. Thanks for the post!
17.
20 Minute Masterpiece: Training a Style Transfer Model with Colab and Fritz(heartbeat.fritz.ai)
1 points by jamesonthecrow 8y ago|0 comments
18.
by jamesonthecrow 8y ago
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
19.
by jamesonthecrow 8y ago
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...
20.
by jamesonthecrow 8y ago
Thats a good point. I mixed up the iPad Pro 2 with the 6th Gen iPad from 2018. The 2018 iPad just squeaked through my threshold for having enough data to be included here, so it's possible that this is just noise. I'll dig into th
21.
by jamesonthecrow 8y ago
Your point about the integration between software and hardware is spot on. Even the Android devices with powerful GPUs or AI accelerators are really difficult to access because Android APIs (even the NNAPI) is really tough to use. Core ML &
22.
by jamesonthecrow 8y ago
The neural engine is a huge boost, but also remember it's a logarithmic scale so the iPhone X is a faster 5x slower than the 6s.
23.
by jamesonthecrow 8y ago
Good catch. Also taking recommendations for better autocorrecting keyboards :)
24.
Announcing Fritz ML Grants – Get $1000 in cloud credits to build ML powered apps(heartbeat.fritz.ai)
8 points by jamesonthecrow 8y ago|0 comments
25.
by jamesonthecrow 8y ago
Congrats to the Numericcal team on the launch! It's great to see new runtimes coming out to improve performance specifically on Android. It's been a real pain for us to get things up to par with Apple devices running Core ML. We’r
26.
Fritz wants to help developers bring machine learning to their mobile apps(techcrunch.com)
11 points by jamesonthecrow 8y ago|0 comments
27.
The Lifecycle of Mobile Machine Learning Models(heartbeat.fritz.ai)
4 points by jamesonthecrow 8y ago|0 comments
28.
Why data scientists and ML engineers should start learning Swift(heartbeat.fritz.ai)
7 points by jamesonthecrow 8y ago|0 comments
29.
TensorFlow Dev Summit 2018 – Just the mobile bits(heartbeat.fritz.ai)
2 points by jamesonthecrow 9y ago|0 comments
30.
by jamesonthecrow 9y ago
Not a joke / easter-egg. RELU6 is an activation function commonly used in deep convolutional neural networks. It comes up fairly often in mobile machine learning cases because it's used in Google's optimized MobileNet archite

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