Deep Java Library (DJL) VS developer-roadmap

It seems to have been picked up by Eclipse and there is also Oracle Labs' Tribuo and Deep Java Library. All seem active, but I don't know much about any of them. I agree it's probably best to follow the community and use a more popular tool like PyTorch.

Although it may be a bit more work, you can do both machine learning and AI in Java. If you are doing deep learning, you can use DeepJavaLibrary (I do work on this one at Amazon). If you are looking for other ML algorithms, I have seen Smile, Tribuo, or some around Spark.

Image preprocessing I know less about, but tokenization is something I've dealt with a bunch. There are a few options, either push the tokenizer into the ONNX model and use MS's ONNX Runtime extensions (we've used this when working with sentencepiece tokenizers), port the tokenizer entirely to Java (we did this for BERT), or use a sentencepiece or HF tokenizers wrapper directly (e.g. Amazon's DJL did this - HF, sentencepiece).

https://djl.ai/ seems very promising. I've played around with it quite a bit, not in real production though. It's a very well documented (https://d2l.djl.ai/) and active project, with Amazon working on it.

Here is link number 1 - Previous text "DJL"

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.

I think DJL also use use it for their tutorials - https://docs.djl.ai/jupyter/tutorial/01_create_your_first_network.html.

AWS Deep Learning more deep learning.

There's a website I personally follow specific for roadmaps called as “roadmap.sh” where all the roadmaps are available. You can check it out, if you like. Here's the link: ▶️ https://roadmap.sh/

If you're starting your journey in web development, here is a roadmap to follow. Understand that Web development is not merely an extension of programming; it's a distinct field that requires a unique blend of coding and visual design skills. Embrace the importance of visual aesthetics from the get-go, and continuously work on improving your design sense. Trust me it will pay off in the long run, and you'll be able to create truly exceptional web experiences that not only function well but also look and feel amazing.

Github developer roadmaps (backend, frontend, cloud ...)

Roadmap.sh (https://roadmap.sh/)

Web Developer-Roadmap GitHub Link: developer-roadmap Crafted by kamranahmedse, this roadmap acts as a compass for developers navigating the vast landscape of technologies. Covering front-end, back-end, and DevOps, it aids developers in charting a learning path aligned with their goals.

✅ kamranahmedse/developer-roadmap: https://github.com/kamranahmedse/developer-roadmap

It may also be beneficial to start with a high-level overview of what there is to learn in a given area, to understand the overall lay of the land - and then use ChatGPT to dig deeper into selected topics. There are many good resources that provide such an overview, like roadmap.sh or my "Definitive Guide to Succeeding as a Professional Dev".

5. Roadmap

Equipment: Find out more about career paths in development at https://roadmap.sh/. For a detailed self-taught program, see Kamran Ahmed’s Computer Science Roadmap: https://roadmap.sh/computer-science.