{"id":19194828,"url":"https://github.com/michabirklbauer/hgb_dse_text_mining","last_synced_at":"2025-04-20T09:32:31.957Z","repository":{"id":168293227,"uuid":"566043599","full_name":"michabirklbauer/hgb_dse_text_mining","owner":"michabirklbauer","description":"Contents for the practical part of the lecture Text Mining","archived":false,"fork":false,"pushed_at":"2024-11-07T08:24:47.000Z","size":62664,"stargazers_count":0,"open_issues_count":0,"forks_count":3,"subscribers_count":1,"default_branch":"master","last_synced_at":"2024-11-07T08:27:00.960Z","etag":null,"topics":["deep-learning","educational","how-to","keras","machine-learning","nlp","python","spacy","tensorflow","text-classification","text-clustering","text-mining"],"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/michabirklbauer.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2022-11-14T21:17:25.000Z","updated_at":"2024-11-07T08:24:52.000Z","dependencies_parsed_at":"2024-11-07T08:33:16.255Z","dependency_job_id":null,"html_url":"https://github.com/michabirklbauer/hgb_dse_text_mining","commit_stats":null,"previous_names":["michabirklbauer/hgb_dse_text_mining"],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/michabirklbauer%2Fhgb_dse_text_mining","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/michabirklbauer%2Fhgb_dse_text_mining/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/michabirklbauer%2Fhgb_dse_text_mining/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/michabirklbauer%2Fhgb_dse_text_mining/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/michabirklbauer","download_url":"https://codeload.github.com/michabirklbauer/hgb_dse_text_mining/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":223823345,"owners_count":17208946,"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":["deep-learning","educational","how-to","keras","machine-learning","nlp","python","spacy","tensorflow","text-classification","text-clustering","text-mining"],"created_at":"2024-11-09T12:03:56.334Z","updated_at":"2024-11-09T12:05:47.940Z","avatar_url":"https://github.com/michabirklbauer.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Introduction to Natural Language Processing\n\nContents for the practical part of the lecture Text Mining @ FH Hagenberg.\n\n## Requirements\n\nLanguage:\n- [Python 3.12](https://www.python.org/downloads/)\n\nIf you want to run the notebooks locally please install the requirements noted in `requirements.txt`:\n- `pip install -r requirements.txt`\n\nFor chapters 5 and 6 you will additionally need `tensorflow` and `transformers`:\n- `pip install tensorflow transformers`\n\n## Chapters\n\n- Chapter 1: spaCy -\u003e [open in Google Colab](https://colab.research.google.com/github/michabirklbauer/hgb_dse_text_mining/blob/master/spaCy.ipynb)\n- Chapter 2: NLTK and Gensim -\u003e [open in Google Colab](https://colab.research.google.com/github/michabirklbauer/hgb_dse_text_mining/blob/master/NLTK_Gensim.ipynb)\n- Chapter 3: Clustering -\u003e [open in Google Colab](https://colab.research.google.com/github/michabirklbauer/hgb_dse_text_mining/blob/master/Features_Clustering.ipynb)\n- Chapter 4: Classification -\u003e [open in Google Colab](https://colab.research.google.com/github/michabirklbauer/hgb_dse_text_mining/blob/master/Classification.ipynb)\n- Chapter 4.1: RF Classification -\u003e [open in RStudio Cloud](https://rstudio.cloud/content/4961423)\n- Chapter 5: Sentiment Analysis -\u003e [open in Google Colab](https://colab.research.google.com/github/michabirklbauer/hgb_dse_text_mining/blob/master/Sentiment.ipynb)\n- Chapter 6: Image Captioning -\u003e [open in Google Colab](https://colab.research.google.com/github/michabirklbauer/hgb_dse_text_mining/blob/master/Captioning.ipynb)\n\nSolutions for the exercises will be available at [michabirklbauer/hgb_dse_text_mining_solutions](https://github.com/michabirklbauer/hgb_dse_text_mining_solutions) *after* the lectures.\n\n## References\n\n- A lot of the neural net slides is taken from [DeepMind's 2020 Deep Learning Lecture Series](https://www.youtube.com/playlist?list=PLqYmG7hTraZCDxZ44o4p3N5Anz3lLRVZF).\n- Chapter 5 is an adaptation of [Google Developers' Machine Learning Foundations](https://colab.research.google.com/github/lmoroney/dlaicourse/blob/master/TensorFlow%20In%20Practice/Course%203%20-%20NLP/Course%203%20-%20Week%202%20-%20Lesson%202.ipynb).\n- Chapter 6 is an adaptation of the official [Keras image captioning example](https://keras.io/examples/vision/image_captioning/).\n\n## Contact\n\n- [micha.birklbauer@gmail.com](mailto:micha.birklbauer@gmail.com)\n- [micha.birklbauer@fh-hagenberg.at](mailto:micha.birklbauer@fh-hagenberg.at)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmichabirklbauer%2Fhgb_dse_text_mining","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmichabirklbauer%2Fhgb_dse_text_mining","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmichabirklbauer%2Fhgb_dse_text_mining/lists"}