pocket-automl-android-tutorial VS Gradient-Samples

Compare pocket-automl-android-tutorial vs Gradient-Samples and see what are their differences.

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pocket-automl-android-tutorial Gradient-Samples
4 -
21 61
- -
0.0 0.0
over 2 years ago over 1 year ago
Java C#
Apache License 2.0 MIT License
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pocket-automl-android-tutorial

Posts with mentions or reviews of pocket-automl-android-tutorial. We have used some of these posts to build our list of alternatives and similar projects.

Gradient-Samples

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

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

What are some alternatives?

When comparing pocket-automl-android-tutorial and Gradient-Samples you can also consider the following projects:

Modern Java - A Guide to Java 8 - Modern Java - A Guide to Java 8

Stanford.NLP for .NET - Stanford NLP for .NET

samples - Sample code referenced by the .NET documentation

Curryfy - Provides strongly typed extensions methods for C# delegates to take advantages of functional programming techniques, like currying and partial application.

Avalonia - Develop Desktop, Embedded, Mobile and WebAssembly apps with C# and XAML. The most popular .NET UI client technology

ShopifySharp - ShopifySharp is a .NET library that helps developers easily authenticate with and manage Shopify stores.

RoboLeague - A car soccer environment inspired by Rocket League for deep reinforcement learning experiments in an adversarial self-play setting.

IL2C - IL2C - A translator for ECMA-335 CIL/MSIL to C language.

SPOT-RNA - RNA Secondary Structure Prediction using an Ensemble of Two-dimensional Deep Neural Networks and Transfer Learning.

TensorFlow.NET - .NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.

simulator - A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles

SciSharp-Stack-Examples - Practical examples written in SciSharp's machine learning libraries