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Enhancing data analysis with Deepnote and Scala

By Filip Žitný

Updated on March 6, 2024

Deepnote supports a variety of programming languages through different kernels. Scala, a powerful language for data science and machine learning, can be integrated into Deepnote using the Almond kernel. We will provide detailed instructions for setting up a Scala kernel with Almond in Deepnote and demonstrate how to use TensorFlow with Scala.

Almond (1).png

Setting up the Scala kernel with Almond

To run Scala in Deepnote, you’ll need to create a custom environment that includes the Almond kernel. Follow these steps to set up the Scala kernel:


FROM almondsh/almond:latest


Tensorflow with Scala

import $ivy.`org.platanios::tensorflow:0.4.0`
import org.platanios.tensorflow.api._

// Start a new session
val session = Session()

// Define a constant tensor
val tensor = tf.constant(Tensor(3.0))

// Run the session to evaluate the tensor
val result = = tensor)

// Print the result

Example notebook


By following the steps outlined in this guide, you can successfully set up and run a Scala kernel with Almond in Deepnote. This allows you to leverage Scala’s powerful features for data science and machine learning tasks, including using TensorFlow with Scala.

If you encounter further issues, please get in touch with our support. Happy conquering the world with AI in Deepnote!

Filip Žitný

Data Scientist

Follow Filip on Twitter, LinkedIn and GitHub

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