Implementing a Natural Language Classifier in iOS with Keras + Core ML

Implementing a Natural Language Classier in iOS with Keras + Core ML An iOS Swift, fully oine Natural Language Classier (NLC) fo ...

run NLC and NLU algorithms on the device, we can provide similar functionality without relying on cloud inference. I thought it ...

SwiftNLCTestClient: A simple test iOS application to play with the wrapper and the Core ML model Detailed instructions: Importer ...

Sample Datasets This folder contains sample datasets with intents and sample utterances from dierent sources: Watson/WatsonConve ...

2. Create the Keras, TensorFlow, Python, Core ML environment: conda env create This environment is created based on the environm ...

4. Check that your prompt changed to: (SwiftNLC) $ 5. Launch Jupyter Notebook: jupyter notebook 6. Open your browser to: http:// ...

from keras.models import Sequential from keras.layers import Dense from keras.optimizers import Adam model = Sequential() model. ...

The wrapper folder contains the following Swift les to implement the one-hot embedding using the NSLinguistic tagger and to easi ...

SwiftNLCModel.swift 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 import Foundation struct BagOf ...

Sample iOS App Once imported, the Swift wrappers les above, using this SwiftNLC Core ML model, will be easy to execute, as in fo ...

More details about how to use Core ML in an iOS app are provided in this tutorial: CoreML, Keras and TensorFlow — a super simple ...

Future As I mentioned, this open source project doesn’t aim to replace much more evolved NLC and NLU platforms such as IBM Watso ...

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