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box_examples

mlbox examples

caffe

Caffe: a fast open framework for deep learning.

ck

Collective Knowledge is a cross-platform customizable Python framework to share artifacts as reusable components with JSON API; assemble experimental workflows (such as multi-objective DNN optimization); automate package installation; crowdsource and reproduce experiments; unify predictive analytics; enable interactive articles. Demo:

ck-caffe2

Integration of Caffe2 to Collective Knowledge workflow framework to provide unified CK JSON API for AI (customized builds across diverse libraries and hardware, unified AI API, collaborative experiments, performance optimization and model/data set tuning):

ck-openvino

Collective Knowledge workflows for OpenVINO Toolkit (Deep Learning Deployment Toolkit)

ck-tensorflow

Collective Knowledge extension for collaboratively evaluating and optimising performance of TensorFlow across diverse hardware, software and data sets (compilers, libraries, tools, models, inputs):

convnet-benchmarks

Easy benchmarking of all publicly accessible implementations of convnets

inference

Reference implementations of inference benchmarks

inference_results_v0.7

kubernetes

Production-Grade Container Scheduling and Management

mlbox

MLBox is a project that reduces friction for machine learning by ensuring that models are easily portable and reproducible.

nn

phd-year2

resources for my PhD

spark

Mirror of Apache Spark

tiny

TinyMLPerf is a benchmark suite for extremely low-power systems such as microcontrollers