TensorSwift VS CoreML-Models

Compare TensorSwift vs CoreML-Models and see what are their differences.

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TensorSwift CoreML-Models
- 2
323 6,221
0.0% -
0.0 2.3
over 6 years ago 10 months ago
Swift Python
MIT License 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.

TensorSwift

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

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

CoreML-Models

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

What are some alternatives?

When comparing TensorSwift and CoreML-Models you can also consider the following projects:

Tensorflow-iOS

Swift-AI - The Swift machine learning library.

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

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

Caffe2

Swift-Brain - Artificial intelligence/machine learning data structures and Swift algorithms for future iOS development. bayes theorem, neural networks, and more AI.

BrainCore - The iOS and OS X neural network framework

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

MLKit - A simple machine learning framework written in Swift 🤖