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https://github.com/Curated-Awesome-Lists/awesome-arabic-nlp

Dive into the world of Arabic NLP with this extensive collection of resources, tools, datasets, and best practices tailored for the Arabic language.
https://github.com/Curated-Awesome-Lists/awesome-arabic-nlp

List: awesome-arabic-nlp

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Dive into the world of Arabic NLP with this extensive collection of resources, tools, datasets, and best practices tailored for the Arabic language.

Host: GitHub
URL: https://github.com/Curated-Awesome-Lists/awesome-arabic-nlp
Owner: Curated-Awesome-Lists
Created: 2023-10-30T17:34:25.000Z (about 1 year ago)
Default Branch: main
Last Pushed: 2023-10-30T17:34:40.000Z (about 1 year ago)
Last Synced: 2024-05-23T07:17:34.327Z (7 months ago)
Topics: arabic, arabic-language, arabic-nlp, awesome-list, machine-learning, natural-language-processing, nlp-resources
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Stars: 6
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

# Awesome arabic-nlp

Welcome to this meticulously curated list of resources dedicated to Natural Language Processing (NLP) in the Arabic language! Arabic is known for its complexity and richness, making advancements in NLP for this language a challenging yet rewarding endeavor.

In this repository, you’ll find a wide array of resources including academic papers, tools, datasets, libraries, and best practices, all specifically tailored to Arabic NLP. Whether you are a researcher, developer, or someone simply interested in applying NLP techniques to Arabic text, this list is an invaluable resource.

The resources included cover a broad spectrum of topics ranging from syntactic analysis, machine translation, named entity recognition, text classification, and much more, all while addressing the unique challenges and characteristics of the Arabic language.

Feel free to contribute to this awesome list by submitting a pull request or suggesting new resources. Together, we can build a comprehensive and up-to-date repository that benefits the entire community working on Arabic NLP. Enjoy your learning journey!

## Table of Contents

- [GitHub projects](#github-projects)
- [Articles & Blogs](#articles-&-blogs)
- [Online Courses](#online-courses)
- [Books](#books)
- [Research Papers](#research-papers)
- [Videos](#videos)
- [Tools & Software](#tools-&-software)
- [Conferences & Events](#conferences-&-events)
- [Slides & Presentations](#slides-&-presentations)
- [Podcasts](#podcasts)

## GitHub projects

- [arabert](https://github.com/aub-mind/arabert) : Pre-trained Transformers for Arabic Language Understanding and Generation (Arabic BERT, Arabic GPT2, Arabic ELECTRA) :star2:
- [ARBML](https://github.com/ARBML/ARBML) : Implementation of many Arabic NLP and CV projects. Providing real-time experience using many interfaces like web, command line, and notebooks. :computer:
- [Shakkala](https://github.com/Barqawiz/Shakkala) : Deep learning for AR text Vocalization - التشكيل الالي للنصوص العربية :chart_with_upwards_trend:
- [arabic-stop-words](https://github.com/mohataher/arabic-stop-words) : Largest list of Arabic stop words on GitHub. أكبر قائمة لمستبعدات الفهرسة العربية على جيت هاب :closed_book:
- [Hadith-Data-Sets](https://github.com/abdelrahmaan/Hadith-Data-Sets) : All Hadith With Tashkil and Without Tashkeel from the Nine Books that are 62,169 Hadith. :book:
- [ar-php](https://github.com/khaled-alshamaa/ar-php) : Set of functionalities enable Arabic website developers to serve professional search, present, and process Arabic content in PHP :globe_with_meridians:
- [Maha](https://github.com/TRoboto/Maha) : Maha is a text processing library specially developed to deal with Arabic text. :scroll:
- [tajmeeaton](https://github.com/mobadarah/tajmeeaton) : تجميعة من المشاريع، وخصوصا مفتوحة المصدر، للنهوض باللغة العربية والأمة. 👨‍💻 👨‍🔬👨‍🏫🧕
- [SOQAL](https://github.com/husseinmozannar/SOQAL) : Arabic Open Domain Question Answering System using Neural Reading Comprehension :question:
- [Arabic-BERT](https://github.com/alisafaya/Arabic-BERT) : Arabic edition of BERT pretrained language models
- [ARBML/masader](https://github.com/ARBML/masader) 🌟🌟🌟 The largest public catalogue for Arabic NLP and speech datasets. Includes +500 datasets annotated with more than 25 attributes.
- [Qutuf/Qutuf](https://github.com/Qutuf/Qutuf) 🌟🌟🌟
Qutuf (قُطُوْف): An Arabic Morphological analyzer and Part-Of-Speech tagger as an Expert System.
- [motazsaad/process-arabic-text](https://github.com/motazsaad/process-arabic-text) 🌟🌟🌟
Pre-process Arabic text (remove diacritics, punctuations, and repeating characters).
- [UBC-NLP/marbert](https://github.com/UBC-NLP/marbert) 🌟🌟🌟
UBC ARBERT and MARBERT Deep Bidirectional Transformers for Arabic.
- [MagedSaeed/farasapy](https://github.com/MagedSaeed/farasapy) 🌟🌟🌟
A Python implementation of the Farasa toolkit.
- [saidziani/Arabic-News-Article-Classification](https://github.com/saidziani/Arabic-News-Article-Classification) 🌟🌟🌟
Automatic categorization of documents based on their content using Supervised Machine Learning.
- [iamaziz/ar-embeddings](https://github.com/iamaziz/ar-embeddings) 🌟🌟🌟
Sentiment Analysis for Arabic Text (tweets, reviews, and standard Arabic) using word2vec.
- [mohabmes/Arabycia](https://github.com/mohabmes/Arabycia) 🌟🌟
Arabic NLP tool for Text Search, POS tagging, Translation, auto-diacritization, and more.
- [adhaamehab/textblob-ar](https://github.com/adhaamehab/textblob-ar) 🌟🌟
Arabic support for textblob library.
- [motazsaad/arabic-sentiment-analysis](https://github.com/motazsaad/arabic-sentiment-analysis) 🌟🌟
Sentiment Analysis in Arabic tweets.

## Articles & Blogs

- [GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP](https://arxiv.org/abs/2305.14976): A large-scale evaluation of ChatGPT on various Arabic NLP tasks, showcasing its performance compared to dedicated models finetuned on Arabic.
- [Diving into Arabic NLP: A Beginner's Guide to Dialect Identification](https://medium.com/@kmelad43/arabic-dialect-identification-774de9315140): An exploration of the challenges and dynamics of Arabic dialect identification in NLP.
- [Camel_tools, a Python Toolkit for Arabic NLP](https://hajar-iba.medium.com/camel-tools-a-python-toolkit-for-arabic-nlp-ba9f1d2e8cb7): A step-by-step explanation of how to use camel_tools for sentiment analysis in Arabic comments.
- [Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT Models](https://arxiv.org/abs/2306.16322): An assessment of GPT-3.5 and GPT-4 models on seven distinct Arabic NLP tasks, highlighting their performance and insights into sentiment analysis.
- [Masader Plus: A New Interface for Exploring+ 500 Arabic NLP](https://arxiv.org/abs/2208.00932): Introducing Masader Plus, a web interface for browsing and exploring the Masader catalog of Arabic NLP datasets.
- [Machine learning advancements in Arabic NLP](https://towardsdatascience.com/machine-learning-advancements-in-arabic-nlp-c6982b2f602b): An overview of effective tools and code examples for Arabic NLP, focusing on social media text.
- [Automate Arabic NLP with Apache Spark](https://towardsdatascience.com/automate-arabic-nlp-with-apache-spark-fdcc2eedade5): Tutorial with code on combining big data with Arabic NLP using Apache Spark and Spark NLP for distributed computing.
- [Arabic NLP: Unique Challenges and Their Solutions](https://towardsdatascience.com/arabic-nlp-unique-challenges-and-their-solutions-d99e8a87893d): A concise overview of the challenges and tools for working with Arabic text in NLP projects, including pre-processing using the camel-tools Python package.
- [Building Yarub Library for Arabic NLP Purposes](https://medium.com/omdena/building-yarub-library-for-arabic-nlp-purposes-8ab099b79c6b): Insights and interesting code snippets on building a library for Arabic NLP using Yarub.
- [Arabic Sentence Embeddings with Multi-Task Learning](https://towardsdatascience.com/arabic-sentence-embeddings-with-multi-task-learning-815801024375): Tutorial on creating Arabic sentence embeddings with Multi-Task Learning for efficient Semantic Textual Similarity.
- [AraBERT: Transformer-based Model for Arabic Language](https://arxiv.org/abs/2003.00104): This paper introduces AraBERT, a BERT-based model specifically pre-trained for Arabic language understanding, achieving state-of-the-art results in various Arabic NLP tasks like Sentiment Analysis and Named Entity Recognition.
- [A Panoramic Survey of Natural Language Processing in the Arab](https://arxiv.org/abs/2011.12631): This survey explores the field of Natural Language Processing (NLP) in Arabic, discussing its unique challenges compared to artificially constructed languages. It covers a wide range of NLP applications and their connections to different disciplines.
- [Post-hoc analysis of Arabic transformer models](https://arxiv.org/abs/2210.09990): This article analyzes and compares transformer models trained on different dialects of Arabic. The study investigates how linguistic information is encoded in these models, revealing insights about word morphology, syntactic dependencies, and capturing nuances of Arabic dialects.
- [Machine Learning and NLP For Arabic: Part Of Speech Tagging](https://medium.com/omdena/machine-learning-and-nlp-for-arabic-part-of-speech-tagging-d8388c1c2e84): This article discusses the use of Deep Learning, specifically Recurrent Neural Networks, for Part-Of-Speech tagging in Arabic texts. It focuses on building open-source NLP libraries and tools for the Arabic language.
- [AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing](https://arxiv.org/abs/2306.06800): This work presents AraMUS, the largest Arabic Pre-trained Language Model (PLM) with 11B parameters, trained on a vast amount of high-quality Arabic textual data. AraMUS achieves state-of-the-art performances on various Arabic classification and generative tasks.
- [Arabic Sentiment Analysis. An Illustrative guide on how to perform sentiment analysis on Arabic texts](https://towardsdatascience.com/arabic-sentiment-analysis-5e21b77fb5ea): This article provides a guide on performing sentiment analysis specifically on Arabic texts, discussing the process and techniques involved.
- [How to Detect and Translate Languages for NLP Project](https://towardsdatascience.com/how-to-detect-and-translate-languages-for-nlp-project-dfd52af0c3b5): This article discusses language challenges that Data Scientists or Machine Learning Engineers may face while working on NLP projects, focusing on detecting and translating multiple languages to a single language.
- [Arabic natural language processing: An overview](https://arxiv.org/abs/1903.02784): This survey provides an overview of the work done on Arabic natural language processing, covering all three main varieties of Arabic and discussing recent resources and tools. It classifies the research papers based on the language variety and associated techniques.
- [Comparing Arabic dialect datasets](https://mapmeld.medium.com/embeddings-for-arabic-dialect-classification-1cf84f336044): This blog post compares Arabic dialect datasets for classification tasks, highlighting the use of embeddings and data flow visualization.
- [Sentiment Analysis in Arabic](https://medium.com/voice-tech-podcast/sentiment-analysis-in-arabic-f08cd20a76d): This article compares open-source libraries for sentiment analysis in Arabic and explores analyzing text in Arabic using Google AutoML tools.

## Online Courses

- [للغة العربية NLP - Arabic Natural Language Processing | Udemy](https://www.udemy.com/course/arabic-natural-language-processing-nlp/)
course that will prepare you to use Natural Language Processing for the Arabic Language. We will cover the fundamentals of Machine Learning/ NLP.
- [البرمجة اللغوية العصبية | NLP | Coursera](https://www.coursera.org/learn/nlp-)
- [Natural Language Processing Specialization 4 courses](https://www.coursera.org/specializations/natural-language-processing)
Offered by deeplearning.ai. Natural Language Processing (NLP) uses algorithms to understand and manipulate human language. This technology is one of the most broadly applied areas of machine learning. By the end of this Specialization, you will be ready to design NLP applications that perform question-answering and sentiment analysis, create tools to translate languages and summarize text, and even build chatbots.
- [Natural Language Processing Course | Udacity](https://www.udacity.com/course/natural-language-processing-nanodegree--nd892)
- [Natural Language Processing with Attention Models Course](https://www.coursera.org/learn/attention-models-in-nlp)
- [Natural Language Processing in TensorFlow | Coursera](https://www.coursera.org/learn/natural-language-processing-tensorflow)
- [NLP - Natural Language Processing with Python | Udemy](https://www.udemy.com/course/nlp-natural-language-processing-with-python/)
- [NLP البرمجة اللغوية العصبية | Udemy](https://www.udemy.com/course/nlp-vkxw/)
- [Learn BERT - most powerful NLP algorithm by Google | Udemy](https://www.udemy.com/course/bert-nlp-algorithm/): Understand and apply Google's game-changing NLP algorithm, BERT, to real-world tasks. Build 2 NLP applications.

## Books

- [Introduction to Arabic Natural Language Processing | SpringerLink](https://link.springer.com/book/10.1007/978-3-031-02139-8) ⭐️
This book provides system developers and researchers in NLP and computational linguistics with necessary information for working with the Arabic language.
- [Recent Advances in NLP: The Case of Arabic Language ](https://link.springer.com/book/10.1007/978-3-030-34614-0) ⭐️
This book addresses common challenges in intelligent natural language processing related to the Arabic language.
- [Arabic natural language processing for Qur'anic research: a ](https://link.springer.com/article/10.1007/s10462-022-10313-2) ⭐️
his article focuses on Arabic natural language processing for Qur'anic research and its implications.
- [Arabic Language Processing: From Theory to Practice: 6th ](https://link.springer.com/book/10.1007/978-3-319-73500-9) ⭐️
This book includes revised selected papers from the 6th International Conference on Arabic Language Processing, covering theory and practice.
- [البرمجة اللغوية العصبية NLP (Arabic Edition) eBook - Amazon.com](https://www.amazon.com/%E2%80%AB%D8%A7%D9%84%D8%A8%D8%B1%D9%85%D8%AC%D8%A9-%D8%A7%D9%84%D9%84%D8%BA%D9%88%D9%8A%D8%A9-%D8%A7%D9%84%D8%B9%D8%B5%D8%A8%D9%8A%D8%A9-NLP%E2%80%AC-Arabic-ebook/dp/B09ZFCMLTY) Arabic edition of the book "Neural Linguistic Programming (NLP)", specifically tailored to Arabic NLP.
- [Natural language processing: state of the art, current trends and ](https://link.springer.com/article/10.1007/s11042-022-13428-4) A research article discussing the state of the art in natural language processing, including work done on Arabic language analysis.
- [Improve Your Writing With NLP: Judith E Pearson: 9781845908614 ](https://www.amazon.com/Improve-Your-Writing-Judith-Pearson/dp/1845908619) This book explores NLP strategies that can transform novice writers into accomplished ones, utilizing resourceful states, beliefs, cognitive strategies, and behaviors of highly skilled writers.
- [Advances in Natural Language Processing: 7th International ](https://link.springer.com/book/10.1007/978-3-642-14770-8) A book in the Lecture Notes in Computer Science series, covering advances in natural language processing.
- [Anaphor Resolution in Arabic using A Hybrid approach: A Machine ](https://www.amazon.com/Anaphor-Resolution-Arabic-Hybrid-approach/dp/613676167X) This book focuses on Arabic anaphora resolution, an important task in NLP applications such as machine translation and information retrieval.
- [A Lexical Database for Modern Standard Arabic Interoperable with a ](https://link.springer.com/chapter/10.1007/978-3-642-23138-4_7) Presents a lexical database for Modern Standard Arabic that addresses the issue of including both obsolete and current words.
- [Tharawat: A Vision for a Comprehensive Resource for Arabic ](https://link.springer.com/chapter/10.1007/978-3-319-18111-0_7) A paper describing a vision for a unified lexical resource for computational processing of Arabic, including its variants.
- [Multilingual Natural Language Processing Applications: From ](https://www.amazon.com/Multilingual-Natural-Language-Processing-Applications/dp/0137151446) This book covers important contributions in multilingual NLP applications from leading researchers in the field.
- [Support Vector Machines based Arabic Language Text ](https://link.springer.com/chapter/10.1007/978-1-4020-8741-7_3) Explores the effectiveness of feature selection methods for Arabic language text classification using Support Vector Machines.
- [Arabic aspect sentiment polarity classification using BERT | Journal ](https://link.springer.com/article/10.1186/s40537-022-00656-6) Discusses the application of Neural Networks for sentiment analysis in Arabic NLP.

## Research Papers

- [GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP](https://arxiv.org/abs/2305.14976) : A large-scale evaluation of ChatGPT on a broad range of Arabic NLP tasks, revealing its performance on 32 diverse natural language understanding and generation tasks.
- [Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT Models](https://arxiv.org/abs/2306.16322) : Assessing the performance of GPT-3.5 and GPT-4 models on seven distinct Arabic NLP tasks, including sentiment analysis, translation, and summarization.
- [Masader Plus: A New Interface for Exploring 500+ Arabic NLP Datasets](https://arxiv.org/abs/2208.00932) : Introducing Masader Plus, a web interface for browsing and exploring Arabic NLP datasets, offering data exploration, filtration, and a simple API.
- [AraVec: A set of Arabic Word Embedding Models for use in Arabic NLP](https://www.sciencedirect.com/science/article/pii/S1877050917321749) : AraVec provides pre-trained distributed word representation models for use in Arabic NLP research.
- [A Comparative Study on Various Deep Learning Techniques for NLP](https://ieeexplore.ieee.org/document/9837659/) : Comparing the performance of different deep learning techniques, such as LSTM and LSTM-CRF, for tasks at the syntactic level in NLP, specifically focusing on Arabic.
- [Arabic Natural Language Processing: An Overview](https://www.sciencedirect.com/science/article/pii/S1319157818310553) : A survey focusing on recent research papers that present and classify advancements in Arabic NLP.
- [A Panoramic Survey of Natural Language Processing in the Arab World](https://arxiv.org/abs/2011.12631) : An overview of natural language processing (NLP) and its application to natural languages such as Arabic, highlighting the interdisciplinary nature of NLP.
- [Arabic Natural Language Processing for Qur'anic Research](https://link.springer.com/article/10.1007/s10462-022-10313-2) : Leveraging NLP techniques for facilitating Qur'anic research.
- [Imam: Word Embedding Model for Islamic Arabic NLP](https://ieeexplore.ieee.org/document/9257931) : Introducing an efficient distributed word representation model for various NLP tasks related to the Islamic domain.
- [The Quest for NLP Applications and Tools: The Case of Standard Arabic and Dialects](https://ieeexplore.ieee.org/document/9675225) : Exploring research efforts in Arabic NLP, focusing on tools, applications, and resources related to both modern standard Arabic and Arabic dialects.
- [AraBERT: Transformer-based Model for Arabic Language](https://arxiv.org/abs/2003.00104) - This paper presents AraBERT, a pre-trained BERT model specifically designed for Arabic language understanding. It achieves state-of-the-art performance on various Arabic NLP tasks.
- [Introduction to Arabic Natural Language Processing](https://link.springer.com/book/10.1007/978-3-031-02139-8) - This book provides an introduction to Arabic Natural Language Processing (NLP) by Nizar Habash, a research scientist at Columbia University.
- [Arabic NLP tools for ontology construction from Arabic text](http://ieeexplore.ieee.org/document/7162980/) - This paper discusses the use of NLP techniques for ontology construction from Arabic text, focusing on the effectiveness of various preprocessing techniques.
- [Graph-based Arabic NLP Techniques: A Survey](https://www.sciencedirect.com/science/article/pii/S1877050918321926) - This paper provides a survey of graph-based techniques used in Arabic NLP, highlighting their role in improving NLP applications.
- [A Review Study for Arabic Machine Learning and Deep Learning](https://ieeexplore.ieee.org/document/9888948/) - This research survey focuses on the use of Deep Learning (DL) methods in Arabic NLP and highlights the evolution of research in this field.
- [AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing](https://arxiv.org/abs/2306.06800) - This paper presents AraMUS, the largest Arabic Pre-trained Language Model (PLM) with state-of-the-art performance on Arabic classification and generative tasks.
- [Exploring NLP web APIs for building Arabic systems](https://ieeexplore.ieee.org/document/8244649) - This paper explores available NLP Web APIs that support the Arabic language and discusses their strengths, weaknesses, and potential future use.
- [Comparative Study of the Most Useful Arabic-supporting Natural](https://ieeexplore.ieee.org/document/8727617) - This paper presents a comparative study of Python and Java libraries for Arabic Natural Language Processing (ANLP) and deep learning, focusing on their suitability for handling Arabic language specificities.
- [Deep learning for Arabic NLP: A survey](https://www.sciencedirect.com/science/article/pii/S1877750317303757) - This survey explores the use of Deep Learning (DL) techniques for NLP, focusing on the Arabic language due to its importance and scarcity of research in this area.
- [Arabic Natural Language Processing: Challenges and Solutions](https://www.researchgate.net/publication/206006010_Arabic_Natural_Language_Processing_Challenges_and_Solutions) - This paper discusses the challenges faced by researchers and developers in building NLP applications for Arabic text and speech.

## Videos

- [Sakhar AlKhereyf - Intro to Arabic NLP | PyData Jeddah - YouTube](https://www.youtube.com/watch?v=R5g6A40U-L8)
- [Grammarly AI-NLP Club #8 - Arabic Natural Language Processing - YouTube](https://www.youtube.com/watch?v=ctvO0-pfppA) - Apr 3, 2019 Speaker: Nizar Habash, an Associate Professor of Computer Science at New York University Abu Dhabi Presentation:\xa0
- [A Short Introduction to Arabic Natural Language Processing by Dr - YouTube](https://www.youtube.com/watch?v=HXMKhPoLXqo)
- [A Short Introduction to Arabic Natural Language Processing (Nizar - YouTube](https://www.youtube.com/watch?v=vQL5CUlbw0k) - Oct 16, 2022 PLENARY PRESENTATION A Short Introduction to Arabic Natural Language Processing Nizar Habash New York University Abu Dhabi Abstract: Arabic\xa0
- [Introduction to Arabic Natural Language Processing (Nizar Habash - YouTube](https://www.youtube.com/watch?v=YH6KEkTSEBA) - Nov 6, 2022 Learn more.
- [NLP with Friends, Featured Friend: Zaid Alyafeai - YouTube](https://www.youtube.com/watch?v=-kPkBFlmACw) - Aug 11, 2021 Fostering Research in Arabic NLP via Open Source Collaboration.
- [Nizar Habash: Introduction to Arabic Natural Language Processing - YouTube](https://www.youtube.com/watch?v=LotoF0UxCJ8) - Nov 6, 2022 Learn more. Open App. Nizar Habash: Introduction to Arabic Natural Language Processing - Part 2. 65 views\xa0
- [Stanford CS224N: Natural Language Processing with Deep - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ) - Jun 22, 2022 For more information about Stanford's Artificial Intelligence professional and graduate programs, visit: [https://stanford.io/ai](https://stanford.io/ai). For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: [https://stanford.io/ai](https://stanford.io/ai)
- [Grammarly AI-NLP Club - YouTube](https://www.youtube.com/playlist?list=PLv_p01hxj9MISx94VP6w6gpV84LhNRO-A) - The idea of Grammarly AI-NLP Club is to bring together Ukrainian and international leaders in the field, specialists interested in AI, Machine Learning,\xa0
- [Conversational AI / NLP - YouTube](https://www.youtube.com/playlist?list=PL5B692fm6--vUjxiSTdlXr7LHDC83bBXb) - Aug 28, 2023 Resources for building and deploying state-of-the-art GPU-accelerated conversational #AI applications. . . . #speechrecognition #NLP #texttospeech
- [Games and NLP - YouTube](https://www.youtube.com/channel/UCNklKPFV0B0IRRQ8ZQflnTQ): Stroll with a Scroll - Coreference Annotation of an Arabic Corpus using a Virtual World Game. Play games and help with research in Natural Language Processing.
- [Games and NLP - YouTube](https://www.youtube.com/@gamesandnlp554): Learn about LingoTowns, a game-with-a-purpose developed by DALI that features mini games for Natural Language Processing research.
- [ChrisMcCormickAI - YouTube](https://www.youtube.com/@ChrisMcCormickAI): Easy-to-follow tutorials on Machine Learning and NLP topics.
- [Nizar Habash: Introduction to Arabic Natural Language Processing - Part 2](https://www.youtube.com/watch?v=LotoF0UxCJ8): Introduction to Arabic NLP by Nizar Habash.
- [Weekly Research Seminar - Prof. Nizar Habash - Arabic & AI](https://www.youtube.com/watch?v=l1Zlz9gjGf4): Research seminar on Arabic NLP by Prof. Nizar Habash.
- [TensorFlow Meetup tunis - Arabic Natural Language Processing](https://www.youtube.com/watch?v=X5TtHaal6As): Exploring various NLP applications in Arabic using TensorFlow.
- [13 - NLP POS Tagging Arabic NLTK - YouTube](https://www.youtube.com/watch?v=SmCngYtiX0s): Lecture on POS tagging in Arabic NLP.
- [Arabic - NLP (Arabic Text classification - Multiclass - Keras - Neural)](https://www.youtube.com/watch?v=iPGG-oHINoQ): Video tutorial on Arabic text classification using Keras and Neural Networks.
- [Nizar Habash Introduction to Arabic Natural Language Processing - Part 1](https://www.youtube.com/watch?v=9_MSq8X8Y00): Part 1 of the introduction to Arabic NLP by Nizar Habash.

## Tools & Software

- [KALIMAT Multipurpose Arabic Corpus](https://sourceforge.net/projects/kalimat/): A corpus that could be of help for researchers working on Arabic NLP. It consists of 20,291 Arabic articles collected from the Omani newspaper Alwatan.
- [EASC (Essex Arabic Summaries Corpus)](https://sourceforge.net/projects/easc-corpus/): Arabic natural language resources containing 153 Arabic articles and 765 human-generated extractive summaries of those articles.
- [Khawas](https://sourceforge.net/projects/kacst-acptool/): An Arabic Corpora Processing Tool for analyzing Arabic corpora.
- [NLTK](http://nltk.sourceforge.net/): A leading platform for building Python programs to work with human language data, including NLP libraries and an active discussion forum.
- [Stanford CoreNLP](https://sourceforge.net/projects/stanford-corenlp.mirror/): A Java suite of core NLP tools, providing linguistic annotations such as tokenization, parts of speech, named entities, sentiment analysis, and more.
- [Arabic Corpus](https://sourceforge.net/projects/newarabiccorpus/): A collection of more than 460 Arab books that can be used for language engineering applications.
- [Osman Arabic Text Readability](https://sourceforge.net/projects/osmanreadability/): An open-source tool for measuring Arabic text readability, allowing users to calculate readability for Arabic text with or without diacritics.
- [Alkhalil Morpho Sys](https://sourceforge.net/projects/alkhalil/): A morphosyntactic parser for Arabic words that can process both vocalized and non-vocalized texts.
- [Best Natural Language Understanding (NLU) Software in 2023 | G2](https://www.g2.com/categories/natural-language-understanding-nlu): Natural language understanding (NLU), a form of natural language processing (NLP), allows users to better understand text through machine learning. This website provides real-time, up-to-date product reviews from verified users to help you choose the right NLU software.
- [spaCy download | SourceForge.net](https://sourceforge.net/projects/spacy.mirror/): spaCy is an industrial-strength NLP library built on the latest research for advanced NLP in Python and Cython. It is designed for real-world applications and can be used for building products and gaining insights.
- [Natural Language Toolkit download | SourceForge.net](https://sourceforge.net/projects/nltk/): The Natural Language Toolkit (NLTK) is a library for NLP. It provides tools and resources for tasks such as tokenization, stemming, lemmatization, parsing, semantic reasoning, and more.

## Conferences & Events

- [Find Intellectual Discussion Events & Groups in Dubai, AE](https://www.meetup.com/find/ae--dubai/intellectual-discussion/): Intellectual discussion events near Dubai, AE. Connect with people who share your interests and attend online or in-person events.
- [Education & Training Events in Israel, List of all Israel Educational](https://10times.com/israel/education-training): Discover upcoming education and training events in Israel. Find conferences, talks, and seminars related to NLP for Hebrew and Arabic.
- [Find Learn Coding Events & Groups in Dubai, AE](https://www.meetup.com/find/ae--dubai/learn-coding/): Explore learn coding events near Dubai, AE. Connect with like-minded individuals and join online or in-person events.
- [10th World Machine Learning and Deep learning Conference](https://machinelearning.conferenceseries.com/) : November 09-10, 2023 Stockholm, Sweden : Renowned Speakers : Dr. Ebrahim Al Alkeem Al Zaabi.
- [Conference in Prague](https://www.meetup.com/sw_groups_13.xml.gz) : June 28, 2022 : A conference discussing various topics related to NLP and Arabic text analysis.

## Slides & Presentations

- [MoM2010: Arabic natural language processing](https://www.slideshare.net/hend.alkhalifa/mom2010-arabic-natural-language-processing): A presentation on the challenges and advancements in Arabic Natural Language Processing, covering grammar, syntactic analysis, and more. 📑
- [Grammarly AI-NLP Club #8 - Arabic Natural Language Processing: Challenges and Solutions](https://www.slideshare.net/grammarly/grammarly-ainlp-club-8-arabic-natural-language-processing-challenges-and-solutions-nizar-habash): A comprehensive discussion on the unique challenges faced in Arabic NLP and the potential solutions. 📑
- [Processing Arabic Text](https://www.slideshare.net/jordanopensource/processing-arabic-text): Slides introducing Natural Language Understanding (NLU) with a focus on Arabic text. 📑
- [Madad: Arabic Annotation Tool for Arabic Text](https://www.slideshare.net/AbeerAlDayel1/madad-arabic-annotation-tool-for-arabic-text): An overview of the Madad annotation tool specifically designed for Arabic NLP tasks. 📑
- [Benchmarking transfer learning approaches for NLP](https://www.slideshare.net/festline/benchmarking-transfer-learning-approaches-for-nlp): A presentation calling for collaboration in applied transfer learning for Arabic text classification tasks. 📑
- [Spark NLP: State of the Art Natural Language Processing at Scale](https://www.slideshare.net/databricks/spark-nlp-state-of-the-art-natural-language-processing-at-scale-239587069): Slides exploring the capabilities and advancements of Spark NLP for Arabic NLP. 📑
- [Language Detection Library for Java](https://www.slideshare.net/shuyo/language-detection-library-for-java): An informative presentation on a language detection library for Java, with a focus on distinguishing between Persian and Arabic languages. 📑
- [Towards Responsible NLP: Walking the walk](https://www.slideshare.net/MonaDiab7/towards-a-responsible-nlp-walking-the-walk): A thought-provoking presentation on responsible NLP practices with insights into how they can be applied to a polyglossic language like Arabic. 📑
- [NLP Literature Survey with focus on Computerized Deception Detection](https://www.slideshare.net/YoavFrancis/litsurvey-nlp): A literature survey on NLP techniques in the context of computerized deception detection. 📑
- [Applied NLP - Poster](https://www.slideshare.net/madhucharis/applied-nlp-poster): A poster presentation showcasing the application of NLP techniques, including Arabic natural language processing. 📑
- [NLP Literature Survey with focus on Computerized Deception Detection](https://www.slideshare.net/YoavFrancis/litsurvey-nlp) - A literature survey on NLP with a focus on computerized deception detection.
- [Habash: Arabic Natural Language Processing](https://www.slideshare.net/jarrar02/habash-arabic-natural-language-processing) - A presentation on Arabic natural language processing, highlighting its challenges and techniques.
- [Lightweight Natural Language Processing (NLP)](https://www.slideshare.net/LithiumTech/lightweight-natural-language-processing-nlp) - A presentation introducing lightweight approaches to natural language processing.
- [Usage of regular expressions in NLP](https://www.slideshare.net/ijreteditor/usage-of-regular-expressions-in-nlp) - A presentation discussing the use of regular expressions in NLP and their applications.
- [Grammarly AI-NLP Club #4 - Understanding and assessing language with neural network models - Marek Rei](https://www.slideshare.net/grammarly/grammarly-ainlp-club-4-understanding-and-assessing-language-with-neural-network-models-marek-rei) - A presentation on understanding and assessing language using neural network models.
- [NLP Based Text Summarization Using Semantic Analysis](https://www.slideshare.net/ijaemseditor/nlp-based-text-summarization-using-semantic-analysis) - A presentation on text summarization using semantic analysis techniques in NLP.
- [NLP communication skills!](https://www.slideshare.net/Visionaryfinance01/nlp-communication-skills) - A presentation focusing on NLP techniques for effective communication and building rapport.
- [Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With Python](https://www.slideshare.net/EdurekaIN/stemming-and-lemmatization-tutorial-natural-language-processing-nlp-with-python-edureka) - A tutorial on stemming and lemmatization in NLP using Python.
- [NLP pipeline in machine translation](https://www.slideshare.net/MarcisPinnis/nlp-pipeline-in-machine-translation) - A presentation discussing the components and process of NLP pipeline in machine translation.
- [NLP](https://www.slideshare.net/sujitdas750331/token-classification) - An overview of NLP basics, including focus on POS tagging and token classification in Bengali language.

## Podcasts

- [NLP Highlights](https://open.spotify.com/show/4tGHzmicSHIVU3ksf5iYv8): In this podcast, researchers from the AllenNLP team at Allen Institute for AI discuss their work in various areas of natural language processing.
- [NLP MasterCLASS](https://open.spotify.com/show/7lXkPjdUAudqVOYGmlPyNW): Hosted by NLP Master Trainers Tina Taylor and Steve Crabb, this podcast explores the amazing ways to use NLP for personal and professional changes.
- [NLP Talks with Laura Evans](https://open.spotify.com/show/2f6GoVWkwCtivpHW0wusSQ): Hosted by Laura Evans, an International Trainer of NLP, this podcast features insightful interviews with people who know how NLP changes lives and offers tips and strategies for success.
- [The Brain Language Podcast](https://open.spotify.com/show/5WuKUAD9huLZr9K5bCu8s6): This podcast introduces NLP concepts that enhance personal and business life, providing golden nuggets of NLP knowledge.
- [WARA Media & Language Podcast](https://open.spotify.com/show/0WMRzlZHJ1hE7YTlRWY1LN): In this podcast, you will hear the latest research within AI in the field of Media, Language, and Gaming, with insights from industry leaders and tech companies.
- [Microsoft Research Podcast](https://open.spotify.com/show/4ndjUXyL0hH1FXHgwIiTWU): This podcast brings you conversations with researchers at Microsoft, discussing cutting-edge advancements in technology.
- [NLP Talks](https://open.spotify.com/show/2pIrOtec11sewDYD6JK3RD): A podcast in Greek about Neuro-Linguistic Programming (NLP) by Athens NLP Studies, aiming to help individuals create positive and lasting changes in their lives.
- [Women in AI](https://open.spotify.com/show/62v63cucHe8HdZD6ooyCOg): A biweekly podcast featuring leading female minds in AI, Deep Learning, and Machine Learning, discussing cutting-edge work, technological advancements, and the impact of AI for social good and diversity in the workplace.

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This initial version of the Awesome List was generated with the help of the [Awesome List Generator](https://github.com/alialsaeedi19/GPT-Awesome-List-Maker). It's an open-source Python package that uses the power of GPT models to automatically curate and generate starting points for resource lists related to a specific topic.