{"id":810,"date":"2025-02-10T21:45:15","date_gmt":"2025-02-10T18:45:15","guid":{"rendered":"https:\/\/ismaelali.net\/?page_id=810"},"modified":"2025-02-10T23:12:44","modified_gmt":"2025-02-10T20:12:44","slug":"natural-language-processing","status":"publish","type":"page","link":"https:\/\/ismaelali.net\/?page_id=810","title":{"rendered":"Natural Language Processing"},"content":{"rendered":"<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"747\" height=\"1000\" src=\"https:\/\/ismaelali.net\/wp-content\/uploads\/2025\/02\/71EiA0VHG3L._UF10001000_QL80_.jpg\" alt=\"\" class=\"wp-image-808\" style=\"width:166px;height:auto\" srcset=\"https:\/\/ismaelali.net\/wp-content\/uploads\/2025\/02\/71EiA0VHG3L._UF10001000_QL80_.jpg 747w, https:\/\/ismaelali.net\/wp-content\/uploads\/2025\/02\/71EiA0VHG3L._UF10001000_QL80_-224x300.jpg 224w\" sizes=\"auto, (max-width: 706px) 89vw, (max-width: 767px) 82vw, 740px\" \/><\/figure>\n<\/div>\n\n\n<h4 class=\"wp-block-heading has-text-align-center\">Course Overview<\/h4>\n\n\n\n<p>This advanced Natural Language Processing (NLP) course explores the interaction between computers and human language, focusing on both the theoretical underpinnings and practical applications of the field. Students will engage with core NLP techniques, including machine learning and deep learning models, to develop skills in text processing, analysis, and translation. The curriculum emphasizes critical thinking about ethical issues such as algorithmic bias and social impacts of NLP technologies. Through lectures, hands-on labs with Python and NLP libraries like TensorFlow and PyTorch, and a capstone project, students will gain the expertise necessary for careers or research in language processing technologies.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Appointment:<\/strong>&nbsp;Request by Email.<\/li>\n\n\n\n<li><strong>Lectures:<\/strong>&nbsp;Once a week (Tuesday @11:00 AM &#8211; 12:30 PM).<\/li>\n\n\n\n<li><strong>Credits<\/strong>: 6<\/li>\n\n\n\n<li><strong>Prerequisites:&nbsp;<\/strong>\n<ul class=\"wp-block-list\">\n<li>Background in machine learning, statistics, and linear algebra.<\/li>\n\n\n\n<li>Proficiency in Python.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Course Website<\/strong>: <a href=\"https:\/\/ismaelali.net\/?page_id=751\">https:\/\/ismaelali.net\/?page_id=751<\/a><\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h4 class=\"wp-block-heading has-text-align-center\">Course Outline<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Overview and Evolution to NLP<\/li>\n\n\n\n<li>Basic Text Processing and Analysis<\/li>\n\n\n\n<li>Statistical Modeling of Language<\/li>\n\n\n\n<li>Machine Learning for NLP<\/li>\n\n\n\n<li>Deep Learning in NLP<\/li>\n\n\n\n<li>Natural Language Generation<\/li>\n\n\n\n<li>Applications of NLP<\/li>\n\n\n\n<li>Ethics and Future Directions<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h4 class=\"wp-block-heading has-text-align-center\">Course Learning Outcomes<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Understand NLP Fundamentals<\/strong>: Explain key concepts and theories in natural language processing.<\/li>\n\n\n\n<li><strong>Apply Machine Learning<\/strong>: Use machine learning and deep learning in NLP tasks.<\/li>\n\n\n\n<li><strong>Develop NLP Applications<\/strong>: Implement applications like text analysis, translation, and speech recognition.<\/li>\n\n\n\n<li><strong>Analyze Text Data<\/strong>: Process and extract insights from large text datasets.<\/li>\n\n\n\n<li><strong>Evaluate NLP Models<\/strong>: Assess model performance and understand ethical implications.<\/li>\n\n\n\n<li><strong>Conduct Research<\/strong>: Perform independent research to solve advanced NLP problems.<\/li>\n\n\n\n<li><strong>Communicate Findings<\/strong>: Present complex NLP concepts and results effectively.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h4 class=\"wp-block-heading has-text-align-center\">Course Schedule<\/h4>\n\n\n\n<figure class=\"wp-block-table aligncenter\"><table><tbody><tr><td><strong>Week<\/strong><strong><\/strong><\/td><td><strong>Topic<\/strong><\/td><\/tr><tr><td>1<strong><\/strong><\/td><td><strong>Introduction to NLP<\/strong><br>Course overview and logistics<br>Introduction to the field of Natural Language Processing<\/td><\/tr><tr><td>2<strong><\/strong><\/td><td><strong>Text Processing Basics<\/strong><br>Tokenization, stemming, lemmatization<br>Part-of-speech tagging and named entity recognition<\/td><\/tr><tr><td>3<strong><\/strong><\/td><td><strong>Text Processing Advanced<\/strong><br>Syntactic parsing and dependency analysis<br>Introduction to semantic analysis<\/td><\/tr><tr><td>4<strong><\/strong><\/td><td><strong>Statistical NLP<\/strong><br>Probabilistic language models (n-grams, smoothing)<br>Information extraction basics<\/td><\/tr><tr><td>5<strong><\/strong><\/td><td><strong>Machine Learning for NLP<\/strong><br>Overview of supervised vs unsupervised learning<br>Feature engineering and dimensionality reduction<\/td><\/tr><tr><td>6<strong><\/strong><\/td><td><strong>Deep Learning Fundamentals<\/strong><br>Introduction to neural networks<br>Basic neural network architectures for NLP<\/td><\/tr><tr><td><strong>7<\/strong><strong><\/strong><\/td><td><strong>Midterm Exam<\/strong><strong><\/strong><\/td><\/tr><tr><td>8<strong><\/strong><\/td><td><strong>Deep Learning in NLP<\/strong><br>Sequence modeling: RNNs, GRUs, and LSTMs<br>Introduction to Transformers and attention mechanisms<\/td><\/tr><tr><td>9<strong><\/strong><\/td><td><strong>Natural Language Generation I<\/strong><br>Generating text: techniques and challenges<\/td><\/tr><tr><td>10<strong><\/strong><\/td><td><strong>Natural Language Generation II<\/strong><br>Advanced NLG applications, dialogue systems, automated storytelling<\/td><\/tr><tr><td>11<strong><\/strong><\/td><td><strong>Applications of NLP I<\/strong><br>Machine translation and multilingual NLP<br>Speech recognition technologies<\/td><\/tr><tr><td>12<strong><\/strong><\/td><td><strong>Applications of NLP II<\/strong><br>Question answering systems and chatbots<br>Sentiment analysis and text classification<\/td><\/tr><tr><td>13<strong><\/strong><\/td><td><strong>Ethics and Impacts<\/strong><br>Discussion on bias, fairness, and ethical issues in NLP<br>Future directions and the societal impact of NLP<\/td><\/tr><tr><td><strong>14<\/strong><strong><\/strong><\/td><td><strong>Final Exam + Project Presentations<\/strong><strong><\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h4 class=\"wp-block-heading has-text-align-center\">Course Assessment<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Assignments (10%):<\/strong>&nbsp;Four assignments involving coding and problem-solving in NLP.<\/li>\n\n\n\n<li><strong>Paper Presentations (20%):<\/strong>&nbsp;Students will present summaries and critiques of assigned research papers.<\/li>\n\n\n\n<li><strong>Midterm Exam (20%):<\/strong>&nbsp;In-class, covering all material up to the exam.<\/li>\n\n\n\n<li><strong>Final Exam (50%):<\/strong>&nbsp;&nbsp;In-class, covering all material of the course.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h4 class=\"wp-block-heading has-text-align-center\">Course Materials<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Reading<\/strong>:\n<ul class=\"wp-block-list\">\n<li>D. Jurafsky and J. H. Martin.&nbsp;<a href=\"https:\/\/web.stanford.edu\/~jurafsky\/slp3\/\"><span style=\"text-decoration: underline;\">Speech and Language Processing (3rd ed. draft).<\/span><\/a><\/li>\n\n\n\n<li>Y. Goldberg.&nbsp;<a href=\"http:\/\/u.cs.biu.ac.il\/~yogo\/nnlp.pdf\"><span style=\"text-decoration: underline;\">A Primer on Neural Network Models for Natural Language Processing.<\/span><\/a><\/li>\n\n\n\n<li>Jacob Eisenstein.&nbsp;<span style=\"text-decoration: underline;\"><a href=\"https:\/\/github.com\/jacobeisenstein\/gt-nlp-class\/blob\/master\/notes\/eisenstein-nlp-notes.pdf\">Natural Language Processing<\/a><\/span>.&nbsp;<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Resources:<\/strong>\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.aclweb.org\/anthology\/\" target=\"_blank\" rel=\"noreferrer noopener\"><span style=\"text-decoration: underline;\">ACL Anthology<\/span><\/a><\/li>\n\n\n\n<li><a href=\"http:\/\/www.ldc.upenn.edu\/\" target=\"_blank\" rel=\"noreferrer noopener\"><span style=\"text-decoration: underline;\">Linguistic Data Consortium<\/span><\/a><\/li>\n\n\n\n<li><a href=\"http:\/\/www-nlp.stanford.edu\/links\/statnlp.html\" target=\"_blank\" rel=\"noreferrer noopener\"><span style=\"text-decoration: underline;\">Stanford List of NLP Resources<\/span><\/a><\/li>\n\n\n\n<li><a href=\"http:\/\/www.cs.cornell.edu\/courses\/cs674\/2002SP\/#resources\" target=\"_blank\" rel=\"noreferrer noopener\"><span style=\"text-decoration: underline;\">Lillian Lee\u2019s List of NLP Resources<\/span><\/a><\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Tools<\/strong>:\n<ul class=\"wp-block-list\">\n<li><em>Python<\/em>: The primary programming language for the course. <a href=\"https:\/\/www.python.org\/\">Python&nbsp;Official&nbsp;Site<\/a><\/li>\n\n\n\n<li><em>NLTK (Natural Language Toolkit)<\/em>: A Python library for working with human language data. <a href=\"http:\/\/www.nltk.org\/\">NLTK&nbsp;Project&nbsp;Page<\/a><\/li>\n\n\n\n<li><em>spaCy<\/em>: Advanced NLP library for performance and scalability. <a href=\"https:\/\/spacy.io\/\">spaCy&nbsp;Official&nbsp;Site<\/a><\/li>\n\n\n\n<li><em>TensorFlow and PyTorch<\/em>: Frameworks for deep learning applications. <a href=\"https:\/\/www.tensorflow.org\/\">TensorFlow&nbsp;Official&nbsp;Site<\/a> , <a href=\"https:\/\/pytorch.org\/\">PyTorch&nbsp;Official&nbsp;Site<\/a><\/li>\n\n\n\n<li><em>Gensim<\/em>: Library for unsupervised topic modeling and natural language processing. <a href=\"https:\/\/github.com\/RaRe-Technologies\/gensim\">Gensim&nbsp;GitHub&nbsp;Repository<\/a><\/li>\n\n\n\n<li><em>Scikit-learn<\/em>: Machine learning library for Python. <a href=\"https:\/\/scikit-learn.org\/\">Scikit-learn&nbsp;Official&nbsp;Site<\/a><\/li>\n\n\n\n<li><em>Hugging Face Transformers<\/em>: Library of pre-trained models for NLP tasks. <a>Hugging&nbsp;Face&nbsp;Transformers<\/a><\/li>\n\n\n\n<li><em>Jupyter Notebook<\/em>: Tool for creating and sharing documents that contain live code, visualizations, and narrative text. <a href=\"https:\/\/jupyter.org\/\">Jupyter&nbsp;Project&nbsp;Page<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h4 class=\"wp-block-heading has-text-align-center\">Teaching Methods<\/h4>\n\n\n\n<p>The course combines theoretical lectures with hands-on lab sessions, using modern NLP tools to apply concepts in practice. Interactive discussions and student-led paper presentations will deepen understanding and engagement with current research. Group projects encourage collaboration and practical problem-solving. Additional online resources and tutorials support self-paced, deeper exploration of topics.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h4 class=\"wp-block-heading has-text-align-center\">Course Policy<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Illness:<\/strong>&nbsp;If you are absent due to illness as a valid excuse, please notify me of your situation at <strong><em>ismael.ali@edu.krd.edu<\/em><\/strong> before (or immediately after) your absence.<\/li>\n\n\n\n<li><strong>Course and Exam Schedule:<\/strong>&nbsp;Student is responsible of constantly following up the schedule for any updated material or any type of assessments, such as exams\/projects.&nbsp;<\/li>\n\n\n\n<li><strong>Etiquette:<\/strong>&nbsp;Attend all the session to be able comprehending the course material. Submit all assignments on-time, no excuse for late submission, except valid illness report.&nbsp;<\/li>\n\n\n\n<li><strong>Late Attendance:&nbsp;<\/strong>No student should enter the hall 10 minutes after start time of the session.&nbsp;<\/li>\n\n\n\n<li><strong>Late Work Policy<\/strong>: Assignments submitted late will incur a penalty of 10% per day, up to a maximum of 5 days. After 5 days, late submissions may not be accepted without prior approval from the instructor.<\/li>\n\n\n\n<li><strong>Academic Integrity and <strong>honesty<\/strong><\/strong>: All students are expected to adhere to the highest standards of academic integrity. Plagiarism, cheating, or any form of dishonesty will not be tolerated. Violations may result in penalties, including a failing grade or further disciplinary actions.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Course Overview This advanced Natural Language Processing (NLP) course explores the interaction between computers and human language, focusing on both the theoretical underpinnings and practical applications of the field. Students will engage with core NLP techniques, including machine learning and deep learning models, to develop skills in text processing, analysis, and translation. The curriculum emphasizes &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/ismaelali.net\/?page_id=810\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Natural Language Processing&#8221;<\/span><\/a><\/p>\n","protected":false},"author":6,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-810","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ismaelali.net\/index.php?rest_route=\/wp\/v2\/pages\/810","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ismaelali.net\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ismaelali.net\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ismaelali.net\/index.php?rest_route=\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/ismaelali.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=810"}],"version-history":[{"count":5,"href":"https:\/\/ismaelali.net\/index.php?rest_route=\/wp\/v2\/pages\/810\/revisions"}],"predecessor-version":[{"id":821,"href":"https:\/\/ismaelali.net\/index.php?rest_route=\/wp\/v2\/pages\/810\/revisions\/821"}],"wp:attachment":[{"href":"https:\/\/ismaelali.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=810"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}