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Turi Create and Concept Behind Image Classification
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Merocode
February 14, 2018
Programming
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130
Turi Create and Concept Behind Image Classification
CocoaHead Berlin
Merocode
February 14, 2018
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Transcript
TURI CREATE CONCEPT BEHIND IMAGE CLASSIFICATION
WHAT WE WANT TO ACHIEVE?
None
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CORE ML
INFERENCE
None
FROM WHERE WE GET THE CORE ML FORMAT MODELS?
> Apple ready-to-use Core ML Models.
> Apple tool (Python Package) to convert known model formats
to Core ML model format. That is covered in that blog post
import coremltools caffe_model = ('EmotiW_VGG_S.caffemodel', 'deploy.prototxt') labels = 'labels.txt' coreml_model
= coremltools.converters.caffe.convert(caffe_model, class_labels=labels, image_input_names='data') coreml_model.save('EmotiW_VGG_S.mlmodel')
WHAT IS A MODEL?
TRAINING
TURI CREATE
> Under the hood of Turi Create is Apache’s MXNet
> Python 2.7, 3.5, 3.6 conda create -n turi python=3.6 source activate turi pip install -U turicreate import turicreate fails on macOS 10.12.6 conda create -n turi python=2.7 pip install -Iv turicreate==4.0
CONVOLUTIONAL NEURAL NETWORKS CNN MODEL Feature extraction part + Classification
part
None
None
None
None
None
None
None
VISUALIZING FEATURE / ACTIVATION MAPS
TRANSFER LEARNING
None
CREATE AND TRAIN A MODEL USING TURI CREATE
SQUEEZENET_V1.1
None
None
None
None
None
15 min.
44 min.
ResNet50
9 min.
17 min.
66 min.
IMAGE AUGMENTATION Invariant Representation Scale Rotation Translation
None
RESOURCES CODE Turi Create Sample Code and Demo Apps
RESOURCES TOOLS Turi Create Anaconda Miniconda
RESOURCES APPLE Turi Create User Guide Turi Create API Documentation
Sample Code: Classifying Images with Vision and Core ML Apple Machine Learning
RESOURCES ARTICLES Convolutional Neural Networks Image Augmentation in Keras
RESOURCES PHOTOS Photo by Gift Habeshaw on Unsplash Elon Musk
SpaceX launch footage
THANK YOU ❤ @_MeroCode_ LET’S LEARN ABOUT MACHINE LEARNING.