Gespeichert in:
| Beteilige Person: | |
|---|---|
| Weitere beteiligte Personen: | |
| Format: | Elektronisch Video |
| Sprache: | Englisch |
| Veröffentlicht: |
[Place of publication not identified]
O'Reilly Media
2019
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/0636920330868/?ar |
| Zusammenfassung: | "Michael Johnson and Norris Heintzelman (Lockheed Martin) share several techniques they've implemented to build classification and NER models from scratch. They lead a tour through this space as it applies to NLP and demonstrate their approach and architecture for the following techniques: Weak supervision for news documents: Using rules base classification alongside deep learning system for text classification; Active learning and human in the loop: Explaining how breakthroughs in transfer learning for NLP have impacted their active learning framework for building an LSTM-based relevance model; Creative training sets: Identifying and cleaning already-labeled datasets, training classifier on "only" positive examples; NER adjudication: Combining knowledge from several annotation sources that leverages the strengths of each source. For each of these topics, Michael and Norris outline the theoretical foundation, the implementation architecture, and tools used and discuss the problems they encountered, so you can avoid making the same mistakes."--Resource description page |
| Beschreibung: | Title from title screen (viewed January 10, 2020) |
| Umfang: | 1 online resource (1 streaming video file (43 min., 17 sec.)) |
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| indexdate | 2025-05-28T09:47:10Z |
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| spelling | Johnson, Michael L. VerfasserIn aut NLP from scratch solving the cold start problem for natural language processing Michael Johnson, Norris Heintzelman [Place of publication not identified] O'Reilly Media 2019 1 online resource (1 streaming video file (43 min., 17 sec.)) zweidimensionales bewegtes Bild tdi rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Title from title screen (viewed January 10, 2020) "Michael Johnson and Norris Heintzelman (Lockheed Martin) share several techniques they've implemented to build classification and NER models from scratch. They lead a tour through this space as it applies to NLP and demonstrate their approach and architecture for the following techniques: Weak supervision for news documents: Using rules base classification alongside deep learning system for text classification; Active learning and human in the loop: Explaining how breakthroughs in transfer learning for NLP have impacted their active learning framework for building an LSTM-based relevance model; Creative training sets: Identifying and cleaning already-labeled datasets, training classifier on "only" positive examples; NER adjudication: Combining knowledge from several annotation sources that leverages the strengths of each source. For each of these topics, Michael and Norris outline the theoretical foundation, the implementation architecture, and tools used and discuss the problems they encountered, so you can avoid making the same mistakes."--Resource description page Strata Conference San Francisco, Calif.) (2019 Natural language processing (Computer science) Machine learning Business logistics Data processing Big data Natural Language Processing Traitement automatique des langues naturelles Apprentissage automatique Logistique (Organisation) ; Informatique Données volumineuses Big data (OCoLC)fst01892965 Business logistics ; Data processing (OCoLC)fst00842765 Machine learning (OCoLC)fst01004795 Natural language processing (Computer science) (OCoLC)fst01034365 Electronic videos Heintzelman, Norris MitwirkendeR ctb O'Reilly & Associates, Verlag pbl |
| spellingShingle | Johnson, Michael L. NLP from scratch solving the cold start problem for natural language processing Strata Conference San Francisco, Calif.) (2019 Natural language processing (Computer science) Machine learning Business logistics Data processing Big data Natural Language Processing Traitement automatique des langues naturelles Apprentissage automatique Logistique (Organisation) ; Informatique Données volumineuses Big data (OCoLC)fst01892965 Business logistics ; Data processing (OCoLC)fst00842765 Machine learning (OCoLC)fst01004795 Natural language processing (Computer science) (OCoLC)fst01034365 Electronic videos |
| subject_GND | (OCoLC)fst01892965 (OCoLC)fst00842765 (OCoLC)fst01004795 (OCoLC)fst01034365 |
| title | NLP from scratch solving the cold start problem for natural language processing |
| title_auth | NLP from scratch solving the cold start problem for natural language processing |
| title_exact_search | NLP from scratch solving the cold start problem for natural language processing |
| title_full | NLP from scratch solving the cold start problem for natural language processing Michael Johnson, Norris Heintzelman |
| title_fullStr | NLP from scratch solving the cold start problem for natural language processing Michael Johnson, Norris Heintzelman |
| title_full_unstemmed | NLP from scratch solving the cold start problem for natural language processing Michael Johnson, Norris Heintzelman |
| title_short | NLP from scratch |
| title_sort | nlp from scratch solving the cold start problem for natural language processing |
| title_sub | solving the cold start problem for natural language processing |
| topic | Strata Conference San Francisco, Calif.) (2019 Natural language processing (Computer science) Machine learning Business logistics Data processing Big data Natural Language Processing Traitement automatique des langues naturelles Apprentissage automatique Logistique (Organisation) ; Informatique Données volumineuses Big data (OCoLC)fst01892965 Business logistics ; Data processing (OCoLC)fst00842765 Machine learning (OCoLC)fst01004795 Natural language processing (Computer science) (OCoLC)fst01034365 Electronic videos |
| topic_facet | Strata Conference San Francisco, Calif.) (2019 Natural language processing (Computer science) Machine learning Business logistics Data processing Big data Natural Language Processing Traitement automatique des langues naturelles Apprentissage automatique Logistique (Organisation) ; Informatique Données volumineuses Business logistics ; Data processing Electronic videos |
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