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DFFML Models for Tensorflow Library

About

DFFML models backed by Tensorflow.

Demo

Demo

This demo was taken before the below steps were updated, the actual accuracy may vary as this video shows accuracy being assessed against the training data. You should try it for yourself and see!

Install

virtualenv -p python3.7 .venv
. .venv/bin/activate
python3.7 -m pip install --user -U dffml[tensorflow]

Usage

wget http://download.tensorflow.org/data/iris_training.csv
wget http://download.tensorflow.org/data/iris_test.csv
head iris_training.csv
sed -i 's/.*setosa,versicolor,virginica/SepalLength,SepalWidth,PetalLength,PetalWidth,classification/g' *.csv
head iris_training.csv
dffml train \
  -model dnn \
  -sources csv=iris_training.csv \
  -classifications 0 1 2 \
  -features \
    def:SepalLength:float:1 \
    def:SepalWidth:float:1 \
    def:PetalLength:float:1 \
    def:PetalWidth:float:1 \
  -num_epochs 3000 \
  -steps 20000 \
  -log debug
dffml accuracy \
  -model dnn \
  -sources csv=iris_test.csv \
  -classifications 0 1 2 \
  -features \
    def:SepalLength:float:1 \
    def:SepalWidth:float:1 \
    def:PetalLength:float:1 \
    def:PetalWidth:float:1 \
  -log critical
dffml predict all \
  -model dnn \
  -sources csv=iris_test.csv \
  -classifications 0 1 2 \
  -features \
    def:SepalLength:float:1 \
    def:SepalWidth:float:1 \
    def:PetalLength:float:1 \
    def:PetalWidth:float:1 \
  -caching \
  -log critical \
  > results.json
head -n 33 results.json

License

DFFML Tensorflow Models are distributed under the terms of the MIT License.

Project details


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