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  1. Getting Started

Tutorials

Deeplearning4j Tutorials

PreviousQuickstartNextQuickstart with MNIST

Last updated 5 years ago

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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 .

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 .

Tutorials covering basic DL4J features

End to End Tutorials showing specific solutions

Functional Programming Principles in Scala
https://community.konduit.ai/
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
Clinical Time Series LSTM
Sea Temperature Convolutional LSTM
Sea Temperature Convolutional LSTM 2
Instacart Multitask Example
Instacart Single Task Example
Cloud Detection Example