kotlindl
kotlingrad
Our great sponsors
kotlindl | kotlingrad | |
---|---|---|
16 | 3 | |
1,391 | 507 | |
1.9% | - | |
5.7 | 3.8 | |
6 months ago | 12 months ago | |
Kotlin | Kotlin | |
Apache License 2.0 | Apache License 2.0 |
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.
kotlindl
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Kotlin Deep Learning Android app - Working
This is a really nice sample app (works out of the box) that Jetbrains have made to showcase the capabilities of this Kotlin Deep Learning library https://github.com/Kotlin/kotlindl
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What libraries do you use for machine learning and data visualizing in scala?
There are Java bindings for TensorFlow, but that's quite low level. I tried to see if I can get some Keras API for Scala, but I'm no expert and haven't had enough time to invest in this, so it's stuck in alpha. Maybe I develop it slow burning over the next year. A bit envious that Kotlin has a Keras-like library.
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KotlinDL 0.3 Is Out With ONNX Integration, Object Detection API, 20+ New Models in ModelHub, and Many New Layers
Could you please add an issue with your use-case and proposed solution? Or write here more details. Do you need just serialization to objects in memory? or just in bytes?
Introducing version 0.3 of our deep learning library, KotlinDL.
The answer to the second question (from the GitHub page):
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Machine Learning in Kotlin (Question)
I'm not in Machine Learning but maybe KotlinDL ?
While KotlinDL seems to be a good solution by Jetbrains, I would personally stick to Java frameworks like DL4J for a better community support and likely more features.
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Numpy for kotlin
For deep learning this is your best bet: https://github.com/jetbrains/kotlindl
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Kotlin Team AMA #3: Ask Us Anything
Please, visit our tutorials and examples for KotlinDL. It covers all possible use-cases for AI implementation at this moment.
Regarding AI: currently, you implement neural networks for solving classification and regression tasks for tabular data, or in Computer Vision with Kotlin Deep Learning Library (KotlinDL).
kotlingrad
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Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia
and that there is a mature library for autodiff https://github.com/breandan/kotlingrad
- Show HN: Shape-Safe Symbolic Differentiation with Algebraic Data Types
What are some alternatives?
KorGE - KorGE Game Engine. Multiplatform Kotlin Game Engine
lets-plot-kotlin - Grammar of Graphics for Kotlin
htmx - </> htmx - high power tools for HTML
Decompose - Kotlin Multiplatform lifecycle-aware business logic components (aka BLoCs) with routing (navigation) and pluggable UI (Jetpack Compose, SwiftUI, JS React, etc.)
tensorflow-keras-scala - Scala-based Keras API for the Java bindings to TensorFlow. Mirror of https://codeberg.org/sciss/tensorflow-keras-scala
kotlin-wrappers - Kotlin wrappers for popular JavaScript libraries
kotlinx-datetime - KotlinX multiplatform date/time library
kotlinx.serialization - Kotlin multiplatform / multi-format serialization
multik - Multidimensional array library for Kotlin
ktor - Framework for quickly creating connected applications in Kotlin with minimal effort
kinference - Running ONNX models in vanilla Kotlin
swift-evolution - This maintains proposals for changes and user-visible enhancements to the Swift Programming Language.