Suyash Joshi - Developing and Deploying ML Models with Java

So you've built / found the perfect Deep Learning model, now how do you put that into production and maintain it? This talk is all about Machine Learning Software Engineering (MLEng) on the Cloud using Java technologies. In particular we will cover :

- Machine Learning Quick Primer (Code & Concepts) using TensorFlow for Java, Tribuo, DJL and PyTorch for Java

- Use Case Deep Dive : Learn how to take pre-trained ML model and deploy it using micro-services architecture (Micronaut framework) on the Cloud

The talk will be hands on with a mix of presentation and live coding. All the code will be available on GitHub after the presentation.

[pinakinchaudhari]

from the recent experience with some of these libraries i am finding DL4J more useful as compared to other as well as more functional. DJL has great document but still makes it very difficult to follow if you are working on very different data source. or having complex structure etc.