Tutorials

Deeplearning4j Tutorials

While Deeplearning4j is written in Java, the Java Virtual Machine (JVM) lets you import and share code in other JVM languages. These tutorials are written in Scala, the de facto standard for data science in the Java environment. There’s nothing stopping you from using any other interpreter such as Java, Kotlin, or Clojure.

If you’re coming from non-JVM languages like Python or R, you may want to read about how the JVM works before using these tutorials. Knowing the basic terms such as classpath, virtual machine, “strongly-typed” languages, and functional programming will help you debug, as well as expand on the knowledge you gain here. If you don’t know Scala and want to learn it, Coursera has a great course named Functional Programming Principles in Scala.

The tutorials are currently being reworked. You will likely find stumbling points. If you need any support while working through them, feel free to ask questions on https://community.konduit.ai/.

Tutorials covering basic DL4J features

Quickstart with MNIST MultiLayerNetwork And ComputationGraph Logistic Regression Built-in Data Iterators Feed Forward Networks Basic Autoencoder Advanced Autoencoder Convolutional Networks Recurrent Networks Early Stopping Layers and Preprocessors Hyperparameter Optimization Using Multiple GPUs

End to End Tutorials showing specific solutions

Clinical Time Series LSTM Sea Temperature Convolutional LSTM Sea Temperature Convolutional LSTM 2 Instacart Multitask Example Instacart Single Task Example Cloud Detection Example

PreviousUntitled NextQuickstart with MNIST

Last updated 4 years ago