QuickQanava
NLTK
| QuickQanava | NLTK | |
|---|---|---|
| 4 | 64 | |
| 1,081 | 13,054 | |
| - | 1.0% | |
| 8.9 | 8.1 | |
| about 1 month ago | 21 days ago | |
| C++ | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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QuickQanava
- There is framework for everything.
- How can i make something like that in Qt5 ? (drag-drop and connect each other)
- Make a canvas with custom, interactable objects
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Should we add a sticky FAQ post?
This is not how to do it. You do not want to have business logic in qml. For this you can subclass QtQuickItem. https://github.com/cneben/QuickQanava is a good example for this.
NLTK
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Building a local AI smart Home Assistant
alternatively, could we not simply split by common characters such as newlines and periods, to split it within sentences? it would be fragile with special handling required for numbers with decimal points and probably various other edge cases, though.
there are also Python libraries meant for natural language parsing[0] that could do that task for us. I even see examples on stack overflow[1] that simply split text into sentences.
[0]: https://www.nltk.org/
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Sorry if this is a dumb question but is the main idea behind LLMs to output text based on user input?
Check out https://www.nltk.org/ and work through it, it'll give you a foundational understanding of how all this works, but very basically it's just a fancy auto-complete.
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Best Portfolio Projects for Data Science
NLTK Documentation
- Where to start learning NLP ?
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Is there a programmatic way to check if two strings are paraphrased?
If this is True, then you need also Natural Language Toolkit to process the words.
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[CROSS-POST] What programming language should I learn for corpus linguistics?
In that case, you should definitely have a look at Python's nltk library which stands for Natural Language Toolkit. They have a rich corpus collection for all kinds of specialized things like grammars, taggers, chunkers, etc.
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Transition to ml, starting with LLM
If not, start with Python's Natural Language Toolkit.
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Learning resources for NLP
Try https://www.nltk.org it runs you through the basics. The book is here
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Which programming language should I learn for NLP and computational linguistics?
In terms of programming languages, Python is a great first programming language. the learnpython subreddit has lots of good recommendations for resources to get started. Once you're comfortable with the language, NLTK would be a good place to start, and the docs have heaps of examples. Check it out https://www.nltk.org/
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Python for stock analysis?
The most popular library to do this is NLTK though I believe you can use some of the popular AI API services today as well. Bloomberg launched one.
What are some alternatives?
nodeeditor - Qt Node Editor. Dataflow programming framework
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
libgrape-lite - 🍇 A C++ library for parallel graph processing (GRAPE) 🍇
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
vg - tools for working with genome variation graphs
bert - TensorFlow code and pre-trained models for BERT
fdg - A Force Directed Graph Drawing Library
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
polyglot - Multilingual text (NLP) processing toolkit
netsci-labs - (In progress) Network science laboratories. Covers graph theory, random graphs and ML on graphs
PyTorch-NLP - Basic Utilities for PyTorch Natural Language Processing (NLP)