Implementing a Natural Language Classifier in iOS with Keras + Core ML
jeff_l
(Jeff_L)
#1
2. Create the Keras, TensorFlow, Python, Core ML environment:
conda env create
This environment is created based on the environment.yml le for
installing Python 2.7, TensorFlow 1.1, Keras 2.0.4, CoreMLTools 0.6.3,
Pandas and other useful Python packages:
name: SwiftNLC
channels:
- !!python/unicode
'defaults'
dependencies:
- python=2.
- pip==9.0.
- numpy==1.12.
- jupyter==1.
- matplotlib==2.0.
- scikit-learn==0.18.
- scipy==0.19.
- pandas==0.19.
- pillow==4.0.
- seaborn==0.7.
- h5py==2.7.
- pip:
- tensorflow==1.6.
- keras==2.1.
- coremltools==0.
- nltk==3.2.
NB NLTK is only needed for the createModelWithNLTKEmbedding
Notebook used on initial testing. The nal
createModelWithNSLinguisticTaggerEmbedding does not use NLTK, as
the word embedding is implemented in Swift on the Embedder module
using the NSLinguisticTagger API.
3. Activate the environment (Mac/Linux):
source activate SwiftNLC
