angular VS spaCy

AngularJS (UI framework built in JavaScript): open (last commit: Apr 12 2022), unsupported Angular 2 to 12 (UI framework built in TypeScript): open, unsupported Angular 13 to 15 (UI framework built in TypeScript): open, supported until May 4 2023, Nov 11 2023 and May 18 2024 AngularDart (UI framework build in Dart): open (last commit: Oct 7 2021?, Today?), supported by community?, they say no Flutter 1: open (last commit: Mar 30 2022), unsupported Flutter 2: open (last commit: Apr 18 2022?), couldn't find if still supported, I assume unsupported Flutter 3: open (last commit: Today), supported

eh.. kinda

Angular Dart. https://pub.dev/packages/angular It seems to be unmaintained, but for a personal project it can fit your needs.

And other related packages are being related now https://github.com/angulardart/angular/releases

development is on branch google https://github.com/angulardart/angular/commits/google

"Angular DART" might be "AngularDart";

By the same mechanism as in the first approach, the custom or default content will be rendered by SlotRendererComponent. The reason why this solution is not working is due to @ContentChildren not being able to query nested ng-contents. Setting { descendants: true } also did not work for me. I found an issue describing the problem for the AngularDart repository so maybe it is related (or I am doing something wrong here ;) ).

2-Dart : Dart Code extends VS Code with support for the Dart programming language and provides tools for effectively editing, refactoring, running, and reloading Flutter mobile apps, and AngularDart web apps.

Let's start with some words about the language. I honestly didn't like Dart at the beginning, when I first read about it some years ago. Dart started as a language that compiled to Javascript, and was advertised as a nice integration to the web ecosystem, especially to Angular, which is still there but not being actively recommended by the AngularDart team.

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.