What is Kotlin DL?

Kotlin DL 0.5 announced! But what is Kotlin DL?

Hi everyone, Did you know that you can do deep learning with Kotlin? Let’s learn together!

Introduction

Kotlin DL is a library that allows developers to build and train deep learning models using the Kotlin programming language. Kotlin is a cross-platform language that is fully compatible with Java and commonly used for developing Android apps. The Kotlin DL library provides a straightforward and intuitive API for integrating machine learning into projects.

Advantages

There are several reasons why developers might choose Kotlin DL for their deep learning projects.

• Kotlin is a popular and widely-used programming language, meaning developers familiar with Kotlin can easily learn Kotlin DL.
• Kotlin DL has a user-friendly API and clear documentation, making it a good choice for developers new to deep learning.
• Kotlin DL is built on top of popular deep learning frameworks such as TensorFlow and PyTorch, allowing developers to leverage the capabilities and flexibility of these frameworks while using Kotlin.

Usage

1. Install the Kotlin DL library by adding the following code to your build.gradle file:

repositories {
    maven {
        url = uri("https://dl.bintray.com/jetbrains/kotlin-native-dependencies")
    }
}


kotlin {
    dl {
        version = "0.5.0"
    }
}

2. Add the Kotlin DL dependency to your project by adding the following code to your build.gradle file:

dependencies {
    implementation("org.jetbrains.kotlinx:kotlinx-dl-api:0.5.0")
}

3. Import the Kotlin DL library into your project by adding the following import statement at the top of your Kotlin file:

import org.jetbrains.kotlinx.dl.api.*

4. Use the Kotlin DL API to build and train your deep learning model. Here is an example of how to create a simple feedforward neural network:

import org.jetbrains.kotlinx.dl.api.core.Sequential
import org.jetbrains.kotlinx.dl.api.core.layer.Dense
import org.jetbrains.kotlinx.dl.api.core.loss.Losses
import org.jetbrains.kotlinx.dl.api.core.optimizer.SGD

val model = Sequential {
    add(Dense(128, inputShape = intArrayOf(28 * 28)))
    add(Dense(10, activation = Activations.Softmax))
}
model.compile(SGD(learningRate = 0.1f), Losses.CategoricalCrossentropy)

5. Use the model to make predictions on new data. Here is an example of how to use the model to make predictions on a single data point:

val data = arrayOf(1.0, 2.0, 3.0, 4.0, 5.0)
val prediction = model.predict(data)

Conclusion

In conclusion, Kotlin DL is a powerful and easy-to-use library for building deep learning models in Kotlin. Its simple API and clear documentation make it a good choice for developers who are new to deep learning, and its compatibility with popular deep learning frameworks such as TensorFlow and PyTorch make it

Glad if it helped, thanks for reading!
I’ll be waiting for your comments and claps! 👏

References

KotlinDL 0.5 Has Come to Android! | The Kotlin Blog

https://kotlinlang.org/docs/data-science-overview.html#kotlin-libraries

Deep Learning With Kotlin: Introducing KotlinDL-alpha | The Kotlin Blog