{"id":15014097,"url":"https://github.com/ninadpatil09/nlp-notebooks","last_synced_at":"2026-03-06T15:03:37.942Z","repository":{"id":231055737,"uuid":"780785969","full_name":"ninadpatil09/NLP-Notebooks","owner":"ninadpatil09","description":"Explore NLP tasks with Python using NLTK, SpaCy \u0026 scikit-learn: Tokenization, Normalization, NER, POS tagging, Encoding, Word embedding.","archived":false,"fork":false,"pushed_at":"2024-04-09T12:48:35.000Z","size":82,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-20T18:23:10.757Z","etag":null,"topics":["natural-language-processing","nlp","nlp-machine-learning","nltk","python","spacy"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ninadpatil09.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-04-02T06:46:51.000Z","updated_at":"2024-11-08T15:25:15.000Z","dependencies_parsed_at":"2024-09-16T01:06:30.279Z","dependency_job_id":"a5215994-c48a-4863-9d3e-d13d4f53e496","html_url":"https://github.com/ninadpatil09/NLP-Notebooks","commit_stats":{"total_commits":15,"total_committers":1,"mean_commits":15.0,"dds":0.0,"last_synced_commit":"cce2d8bef64dd106e7b6c0509f8239798f32e0cb"},"previous_names":["ninja-09/nlp-notebooks"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ninadpatil09%2FNLP-Notebooks","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ninadpatil09%2FNLP-Notebooks/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ninadpatil09%2FNLP-Notebooks/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ninadpatil09%2FNLP-Notebooks/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ninadpatil09","download_url":"https://codeload.github.com/ninadpatil09/NLP-Notebooks/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239926837,"owners_count":19719785,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["natural-language-processing","nlp","nlp-machine-learning","nltk","python","spacy"],"created_at":"2024-09-24T19:45:11.120Z","updated_at":"2026-03-06T15:03:37.935Z","avatar_url":"https://github.com/ninadpatil09.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# NLP-Notebooks\n\nThis repository contains notebooks showcasing various Natural Language Processing (NLP) tasks implemented using Python and popular NLP libraries such as NLTK, SpaCy, and scikit-learn. The notebooks cover a wide range of NLP tasks including tokenization, normalization (stemming and lemmatization), bags of words, named entity recognition (NER), part-of-speech (POS) tagging, different encoding techniques, word embedding using Word2Vec and GloVe, and TF-IDF (Term Frequency-Inverse Document Frequency).\n\n## Notebooks\n\n- [Tokenization](Tokenization.ipynb) : Notebook demonstrating tokenization techniques using NLTK and SpaCy.\n- [Stemming](Stemming.ipynb) : Implemented stemming techniques with NLTK and SpaCy in Python\n- [Lemmatization](Lemmatization.ipynb) : Explored lemmatization methods in Python using NLTK and SpaCy \n- [Named Entity Recognition](NER.ipynb) : Performed Named Entity Recognition (NER) using NLTK and SpaCy in Python. Understand how to identify and extract named entities such as person names, organization names, locations, etc.\n- [Part-of-Speech Tagging](POS_Tagging.ipynb) : Implemented POS tagging techniques with NLTK and SpaCy in Python. Learn how to assign grammatical categories to words in a text corpus, such as noun, verb, adjective, etc.\n- [Stopwords](Stopwords.ipynb) : Demonstrated stopwords removal techniques using NLTK and SpaCy in Python. Understand how to filter out common words that do not carry significant meaning in text analysis tasks.\n\n  Encoding Techniques -\n  - [One Hot Encoding](OneHotEncoding.ipynb) : Performed OHE on text documents into binary vectors, demonstrated using NLTK and SpaCy in Python.\n  - [Bag of Words](BagofWords.ipynb) :  Represented text documents as vectors based on word frequency, using NLTK and SpaCy in Python.\n  - [TF-IDF](TF_IDF.ipynb) : Assigns scores to words in documents based on their frequency (term frequency) and rarity (inverse document frequency), using NLTK and SpaCy in Python.\n  \n  Word Embedding -\n  - [Word2Vec](Word2Vec.ipynb) : Implementated of Word2Vec in Python using both pretrained and scratch-built models.\n  - [Avg Word2Vec](AvgWord2Vec.ipynb) : Utilization of average Word2Vec embeddings in Python, demonstrating efficient word embedding techniques for natural language processing tasks.\n  - [GloVe](GloVe.ipynb) : Utilized Stanford's pre-trained GloVe model for efficient word embedding in natural language processing tasks.\n  - [FastText](FastText.ipynb) :  Leveraged Gensim and the FastText library for effective text representation and classification using subword information and Skipgram architecture.\n\n## Requirements\n\n- Python 3\n- Jupyter Notebook/Google Colab\n- NLTK\n- SpaCy\n- Scikit learn\n- Gensim\n  \n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE.md) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fninadpatil09%2Fnlp-notebooks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fninadpatil09%2Fnlp-notebooks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fninadpatil09%2Fnlp-notebooks/lists"}