Bender VS Awesome-Mobile-Machine-Learning

Compare Bender vs Awesome-Mobile-Machine-Learning and see what are their differences.

Awesome-Mobile-Machine-Learning

A curated list of awesome mobile machine learning resources for iOS, Android, and edge devices. (by fritzlabs)
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Bender Awesome-Mobile-Machine-Learning
- 1
1,783 1,231
0.2% -
3.4 4.2
5 months ago almost 3 years ago
Swift
Unknown MIT 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.

Bender

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

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

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.

What are some alternatives?

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

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

Swift-AI - The Swift machine learning library.

Tensorflow-iOS

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

Caffe2

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

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

AIToolbox - A toolbox of AI modules written in Swift: Graphs/Trees, Support Vector Machines, Neural Networks, PCA, K-Means, Genetic Algorithms