PipelineAI Quick Start (CPU + GPU)

Train and Deploy your ML and AI Models in the Following Environments:

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Install mlflow via pip install mlflow

Python 3.6 (tensorflow is currently unsupported by Python 3.7)

Install tensorflow via pip install tensorflow

Install keras via pip install keras

Install PIL via pip install pillow

mlflow run example/flower_classifier --no-conda

The MLflow Tracking UI will run at http://localhost:5000. Start it with:

mlflow ui

Note: mlflow ui will not run from within the cloned repo.

Name		Name	Last commit message	Last commit date
Latest commit History 61 Commits
aggregate		aggregate
autoroute		autoroute
autoscale/rps-v1/model		autoscale/rps-v1/model
bash/zz_experimental/script-v1/model		bash/zz_experimental/script-v1/model
caffe		caffe
java/airbnb/model		java/airbnb/model
keras		keras
mxnet/mnist-v1/model		mxnet/mnist-v1/model
optimize_me/linear/cpu		optimize_me/linear/cpu
pmml/airbnb/model		pmml/airbnb/model
python		python
pytorch		pytorch
scikit		scikit
spark		spark
tensorflow		tensorflow
xgboost		xgboost
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md