libpython-clj VS spaCy

It’s also worth noting that Clojure has libpython-clj (https://github.com/clj-python/libpython-clj) which offers an interface with Python from another lisp. Here are some advanced ML and dataviz examples using that lib: https://github.com/gigasquid/libpython-clj-examples.

Basically, you take a programming language and make it work on a platform that meant to be programmed using a different PL. Clojure is hosted by design - it's not Java, but can be used to program for JVM. It ain't Javascript, but can be used to target nodejs and browser; not an [official] CLR language, but you can write .Net programs. You can use Clojure to make Flutter apps with ClojureDart. You can integrate Python into Clojure with libpython-clj. Or write Clojure to target Erlang/OTP; or Rust; or R; There's even a clojure-like language for Lua - Fennel.

There's something about Clojure people like so much, they want it to work atop any platform.

https://github.com/Tensegritics/ClojureDart

https://github.com/clj-python/libpython-clj

https://github.com/clojerl/clojerl

https://github.com/clojure-rs/ClojureRS

https://github.com/scicloj/clojisr

https://fennel-lang.org

There's this project that's used a lot for taking advantage of Pythons ecosystem through Clojure JVM. https://github.com/clj-python/libpython-clj

Ahh, makes sense. Well, if you ever wanna steal some of python's thunder, libpython-clj worked great for me lol. Supposedly py4cl fills a similar role in Common Lisp.

High quality interop with any python library via libpython-clj including, but not limited to, keras, numpy, matplotlib, and pandas. This includes zero copy paths from many of those.

libpython-clj now has Java bindings...go tell all your Java friends!

Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):

SpaCy: An open-source library providing tools for advanced NLP tasks like tokenization, entity recognition, and part-of-speech tagging.

spaCy https://spacy.io/

In this article, I'm going to walk through a sentiment analysis project from start to finish, using open-source Amazon product reviews. However, using the same approach, you can easily implement mass sentiment analysis on your own products. We'll explore an approach to sentiment analysis with one of the most popular Python NLP packages: spaCy.

Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post.

The steps described in "LLM pragmatism" are basically what I see my data science friends doing — it's hard to justify the cost (money and latency) in using LLMs directly for all tasks, and even if you want to you'll need a baseline model to compare against, so why not use LLMs for dataset creation or augmentation in order to train a classic supervised model?

[0] https://spacy.io/

[1] https://prodi.gy/

spaCy

I chose spacy. Although it's not state of the art, it's very well established and stable.