Deep Java Library (DJL)
quine-relay
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Deep Java Library (DJL) | quine-relay | |
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13 | 49 | |
3,830 | 13,750 | |
1.9% | - | |
9.4 | 6.4 | |
1 day ago | 2 months ago | |
Java | Ruby | |
Apache License 2.0 | - |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Deep Java Library (DJL)
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Is deeplearning4j a good choice?
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.
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Just want to vent a bit
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.
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Best way to combine Python and Java?
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).
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Anybody here using Java for machine learning?
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.
- Good document classification library in Java
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2021-09 - Plans & Hopes for Clojure Data Science
Here is link number 1 - Previous text "DJL"
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[D] Java vs Python for Machine learning
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.
- Does Java has similar project like this one in C#? (ml, data)
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If it gets better w age, will java become compatible for machine learning and data science?
I think DJL also use use it for their tutorials - https://docs.djl.ai/jupyter/tutorial/01_create_your_first_network.html.
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Machine learning on JVM
AWS Deep Learning more deep learning.
quine-relay
- Quine Relay: An uroboros program with 100 programming languages
- Quine Relay – An uroboros program with 100 programming languages
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Radiation-hardened Quine: A quine that works after any one character is deleted
If there were more languages, then it'd be `console.log("System.out.println({python_source})")`, etc. The problem then becomes quoting and escaping inner quotes. I managed to avoid the problem by using both single and double quotes, and relying on Python's `repr` also giving valid JS strings, but if I had to add one more language I'd have problems.
I still think the Quine Relay is a tour de force, but for different reasons. It's not 128 quines in different languages, but an incredibly robust system for quoting and escaping strings in 128 different languages.
[1] https://github.com/mame/quine-relay/blob/master/src/code-gen...
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JavaScript forbidden practices. Part 4: self-documenting code
One of the most impressive works I've seen: https://github.com/mame/quine-relay
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High Te/Ti users, explain to me a fact (scientific/business/practical...) in stupid terms.
"Quine" is a type of program, when executed, will output itself (it's actually it's source code). It's very hard to write one. And this guy wrote a loop quine. It supposed to work like this: * A program in language A output a program in language B * The program in language B output a program in language C * The program in language C output the same program in language A which we started with
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What do you do to achieve this catastrophy?
Or a Quine relay.
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It’s worse on mondays for some reason…
Why use a couple of languages, when you can use 128 of them simultaneously? https://github.com/mame/quine-relay
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Weird Ones: 30 years of Brainfuck
Quine relay [1] is to this day the most "I will never understand this" brainfuck project I have ever seen.
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AI Artist
Go look at a programming quine and tell me it isn't art.
What are some alternatives?
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
WLED - Control WS2812B and many more types of digital RGB LEDs with an ESP8266 or ESP32 over WiFi!
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
ox - An independent Rust text editor that runs in your terminal!
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
chinese-poetry - The most comprehensive database of Chinese poetry 🧶最全中华古诗词数据库, 唐宋两朝近一万四千古诗人, 接近5.5万首唐诗加26万宋诗. 两宋时期1564位词人,21050首词。
Tribuo - Tribuo - A Java machine learning library
OpenCorePkg - OpenCore bootloader
CoreNLP - CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.
cp-ddd-framework - 轻量级DDD正向/逆向业务建模框架,支撑复杂业务系统的架构演化!
Apache Flink - Apache Flink
yt-dlc - media downloader and library for various sites.