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Moath Erqsous's Projects

3in1-sudoku-web-app icon 3in1-sudoku-web-app

A multi-dimensional Flask-based Sudoku web application that allows users the option to generate and play a random Sudoku, input their own Sudokus to play, or solve any Sudoku of their choosing.

8-puzzle icon 8-puzzle

Lisp program for solving the 8-puzzle tile game

chatgpt icon chatgpt

An experimental open-source attempt to make GPT-4 fully autonomous.

collabortweet icon collabortweet

Collaborative web framework for analyzing text (e.g., tweets). Supports standard labeling and pairwise comparison.

encord-active icon encord-active

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling to supercharge model performance.

fastai icon fastai

The fastai deep learning library

hugo icon hugo

The world’s fastest framework for building websites.

hugo-profile icon hugo-profile

A highly customizable and mobile first Hugo template for personal portfolio and blog.

lime icon lime

Lime: Explaining the predictions of any machine learning classifier

nlp-datasets icon nlp-datasets

Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)

practical-nlp-code icon practical-nlp-code

Official Repository for Code associated with 'Practical Natural Language Processing' book by O'Reilly Media

tensor2tensor icon tensor2tensor

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

textblob icon textblob

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

universal-data-tool icon universal-data-tool

Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

vadersentiment icon vadersentiment

VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.

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