```fun main() { val X = -1.0f..1.0f step 0.01f...

# kotlindl

[Christian Babsek]

fun main() {
    val X = -1.0f..1.0f step 0.01f
    val Y = X.map { it.pow(2) }

    val dataset = OnHeapDataset.create(
        features = X.map { floatArrayOf(it) }.toTypedArray(),
        labels = Y.toList().toFloatArray()
    )

    val model = Sequential.of(
        Input(1),
        Dense(4, activation = Activations.Linear),
        Dense(1, activation = Activations.Linear)
    )

    model.use {
        it.compile(
            optimizer = Adam(),
            loss = Losses.MSE,
            metric = Metrics.ACCURACY
        )
        it.summary()
        repeat(1000) { i ->
            val history = it.fit(
                dataset = dataset,
                epochs = 100
            )
            println(it.evaluate(dataset))
            listOf(-1f, -0.5f, 0f, 0.5f, 1f)
                .map { v -> v to it.predict(floatArrayOf(v)) }
                .forEach { println("Prediction for ${it.first}: ${it.second}") }
        }
    }
}

Its really just a first try and no good code