Awesome-Mobile-Machine-Learning vs Caffe2

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Awesome-Mobile-Machine-Learning		Caffe2
	Project
1	Mentions	-
1,231	Stars	8,443
-	Growth	-
4.2	Activity	0.0
almost 3 years ago	Latest Commit	over 5 years ago
	Language	Jupyter Notebook
MIT License	License	-

The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Awesome-Mobile-Machine-Learning

Posts with mentions or reviews of Awesome-Mobile-Machine-Learning. We have used some of these posts to build our list of alternatives and similar projects.

Mobile ML general
1 project | /r/createml | 12 Jan 2021

Caffe2

Posts with mentions or reviews of Caffe2. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Caffe2 yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing Awesome-Mobile-Machine-Learning and Caffe2 you can also consider the following projects:

Swift-AI - The Swift machine learning library.

Caffe - Caffe: a fast open framework for deep learning.

CoreML-Models - Largest list of models for Core ML (for iOS 11+)

mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

CoreML-samples - Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools.

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

SwiftCoreMLTools - A Swift library for creating and exporting CoreML Models in Swift

Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!

Bender - Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.

Porcupine - On-device wake word detection powered by deep learning

DL4S - Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux