Preprocessing unstructured data for LLMs and RAG systems:
This course offers an in-depth exploration of preprocessing unstructured data for large language models and retrieval-augmented generation systems. You'll start by setting up your development environment and configuring essential APIs, ensuring a solid technical foundation. Next, you'll di...
Gespeichert in:
| Weitere beteiligte Personen: | |
|---|---|
| Format: | Elektronisch Video |
| Sprache: | Englisch |
| Veröffentlicht: |
[Birmingham, United Kingdom]
Packt Publishing
[2024]
|
| Ausgabe: | [First edition]. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781836642930/?ar |
| Zusammenfassung: | This course offers an in-depth exploration of preprocessing unstructured data for large language models and retrieval-augmented generation systems. You'll start by setting up your development environment and configuring essential APIs, ensuring a solid technical foundation. Next, you'll dive into data preprocessing techniques, tackling challenges like content extraction, cleaning, and data normalization, making your data ready for advanced AI models. As you progress, the course provides hands-on experience with various document types such as PDFs, HTML, and PPTX files. You'll learn to transform these unstructured formats into structured data that AI systems can easily process. Advanced modules cover chunking, metadata extraction, and handling complex documents using cutting-edge techniques like visual transformers and document layout detectors. The final section guides you in building a complete RAG system using the skills acquired throughout the course. You'll preprocess diverse documents, implement semantic similarity searches, and save elements to a vector database. By the end, you'll be equipped to create intelligent data pipelines and interact with your documents using AI, significantly enhancing your data-driven projects. |
| Beschreibung: | Online resource; title from title details screen (O'Reilly, viewed October 9, 2024) |
| Umfang: | 1 Online-Ressource (1 video file (3 hr., 2 min.)) sound, color. |
| ISBN: | 9781836642930 1836642938 |
Internformat
MARC
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Datensatz im Suchindex
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| discipline | Informatik |
| edition | [First edition]. |
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| id | ZDB-30-ORH-109654609 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-17T11:22:07Z |
| institution | BVB |
| isbn | 9781836642930 1836642938 |
| language | English |
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| physical | 1 Online-Ressource (1 video file (3 hr., 2 min.)) sound, color. |
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| publishDate | 2024 |
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| publisher | Packt Publishing |
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| spelling | Preprocessing unstructured data for LLMs and RAG systems [First edition]. [Birmingham, United Kingdom] Packt Publishing [2024] 1 Online-Ressource (1 video file (3 hr., 2 min.)) sound, color. zweidimensionales bewegtes Bild tdi rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; title from title details screen (O'Reilly, viewed October 9, 2024) This course offers an in-depth exploration of preprocessing unstructured data for large language models and retrieval-augmented generation systems. You'll start by setting up your development environment and configuring essential APIs, ensuring a solid technical foundation. Next, you'll dive into data preprocessing techniques, tackling challenges like content extraction, cleaning, and data normalization, making your data ready for advanced AI models. As you progress, the course provides hands-on experience with various document types such as PDFs, HTML, and PPTX files. You'll learn to transform these unstructured formats into structured data that AI systems can easily process. Advanced modules cover chunking, metadata extraction, and handling complex documents using cutting-edge techniques like visual transformers and document layout detectors. The final section guides you in building a complete RAG system using the skills acquired throughout the course. You'll preprocess diverse documents, implement semantic similarity searches, and save elements to a vector database. By the end, you'll be equipped to create intelligent data pipelines and interact with your documents using AI, significantly enhancing your data-driven projects. Natural language processing (Computer science) Artificial intelligence Machine learning Traitement automatique des langues naturelles Intelligence artificielle Apprentissage automatique artificial intelligence Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet Dichone, Paulo MitwirkendeR ctb Packt Publishing, Verlag pbl |
| spellingShingle | Preprocessing unstructured data for LLMs and RAG systems Natural language processing (Computer science) Artificial intelligence Machine learning Traitement automatique des langues naturelles Intelligence artificielle Apprentissage automatique artificial intelligence Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet |
| title | Preprocessing unstructured data for LLMs and RAG systems |
| title_auth | Preprocessing unstructured data for LLMs and RAG systems |
| title_exact_search | Preprocessing unstructured data for LLMs and RAG systems |
| title_full | Preprocessing unstructured data for LLMs and RAG systems |
| title_fullStr | Preprocessing unstructured data for LLMs and RAG systems |
| title_full_unstemmed | Preprocessing unstructured data for LLMs and RAG systems |
| title_short | Preprocessing unstructured data for LLMs and RAG systems |
| title_sort | preprocessing unstructured data for llms and rag systems |
| topic | Natural language processing (Computer science) Artificial intelligence Machine learning Traitement automatique des langues naturelles Intelligence artificielle Apprentissage automatique artificial intelligence Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet |
| topic_facet | Natural language processing (Computer science) Artificial intelligence Machine learning Traitement automatique des langues naturelles Intelligence artificielle Apprentissage automatique artificial intelligence Instructional films Nonfiction films Internet videos Films de formation Films autres que de fiction Vidéos sur Internet |
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