CoreML-samples VS TensorSwift

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

CoreML-samples

Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools. (by ytakzk)

TensorSwift

A lightweight library to calculate tensors in Swift, which has similar APIs to TensorFlow's (by qoncept)
Our great sponsors
  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • SaaSHub - Software Alternatives and Reviews
CoreML-samples TensorSwift
- -
41 323
- 0.0%
0.0 0.0
over 6 years ago over 6 years ago
Jupyter Notebook Swift
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.

CoreML-samples

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

We haven't tracked posts mentioning CoreML-samples yet.
Tracking mentions began in Dec 2020.

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.

What are some alternatives?

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

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

Tensorflow-iOS

Caffe2

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

Awesome-Mobile-Machine-Learning - A curated list of awesome mobile machine learning resources for iOS, Android, and edge devices.

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

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

Swift-AI - The Swift machine learning library.

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