java VS wasmer-java

There are Java bindings for TensorFlow, but that's quite low level. I tried to see if I can get some Keras API for Scala, but I'm no expert and haven't had enough time to invest in this, so it's stuck in alpha. Maybe I develop it slow burning over the next year. A bit envious that Kotlin has a Keras-like library.

Hope this is not too late to answer your question. In theory there are no official Java tutorials for Tensorflow 2. The Java implementation is still under development at https://github.com/tensorflow/java

To give a contrasting perspective, I think the Java ecosystem is much better suited for many data science tasks, and has a growing and well-maintained set of libraries for general purpose machine learning. I won't list them all, but TF-Java, DJL et al. have implementations of many modern architectures and there are a number of excellent libraries (CoreNLP, Lucene et al.) for working with text.

Here's the latest java git repo https://github.com/tensorflow/java

Great idea! Luckily, there's https://github.com/wasmerio/wasmer-java, so you can easily run that wasm binary in your JVM running in your browser!

The biggest integration library is wasmer. It's intended as a server runtime for wasm. The official port wasmer-java has the problem of not supporting imports and that's also not to be implemented in the near future (they are restructuring the wasmer library according to this issue), the other is wasmer-jni. An inofficial jni-binding for the wasmer base implementation. Less nice to use, but feature complete.

Check how the rust compiler can target Web Assembly and then have a look at https://github.com/wasmerio/wasmer-java

If your savvy with WASM I think you could compile to wasm and make java bindings with https://github.com/wasmerio/wasmer-java