Extracting Structured Data From PDFs | Full Python AI project for beginners (ft Docker)

Thu Vu ยท Beginner ยท๐Ÿ“Š Data Analytics & Business Intelligence ยท1y ago
Skills: BI Tools53%

About this lesson

Download Docker Desktop ๐Ÿ‘‰ https://dockr.ly/4e7k8tQ Containerize your generative AI application ๐Ÿ‘‰ https://dockr.ly/3TsIndW Github repo: ๐Ÿ‘‰ https://github.com/thu-vu92/structured-rag-pdf.git Master Python for AI Projects ๐Ÿ‘‰ https://python-course-earlybird.framer.website/?&utm_source=pdf2dataai Get regular data science/ AI content in your inbox: https://thu-vu.ck.page/49c5ee08f6 ๐Ÿ”‘ TIMESTAMPS โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€ 0:00 - Introduction to RAG 1:03 - Video outline 2:18 - Why RAG is useful 5:05 - Setting up project & Get API key 10:48 - Define LLM 12:16 - Process PDF document 13:43 - Split document 17:11 - Create text embeddings 20:18 - Vector database 23:43 - Query database 24:32 - Generate response 28:49 - Create Streamlit app 29:36 - Deploy app with Docker ๐Ÿ‘ฉ๐Ÿปโ€๐Ÿ’ป COURSES & RESOURCES โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€ ๐Ÿ“– Google Advanced Data Analytics Certificate ๐Ÿ‘‰ https://imp.i384100.net/anK9zZ ๐Ÿ“– Google Data Analytics Certificate ๐Ÿ‘‰ https://imp.i384100.net/15v9y6 ๐Ÿ“– Learn SQL Basics for Data Science Specialization ๐Ÿ‘‰ https://imp.i384100.net/AovPnJ ๐Ÿ“– Excel Skills for Business ๐Ÿ‘‰ https://coursera.pxf.io/doPaoy ๐Ÿ“– Machine Learning Specialization ๐Ÿ‘‰ https://imp.i384100.net/RyjykN ๐Ÿ“– Data Visualization with Tableau Specialization ๐Ÿ‘‰https://imp.i384100.net/n15XWR ๐Ÿ“– Deep Learning Specialization ๐Ÿ‘‰ https://imp.i384100.net/zavBA0 ๐Ÿ“– Mathematics for Machine Learning and Data Science Specialization ๐Ÿ‘‰ https://imp.i384100.net/LXK0gj ๐Ÿ“– Applied Data Science with Python ๐Ÿ‘‰ https://imp.i384100.net/gbxOqv As a member of the Amazon and Coursera Affiliate Programs, I earn a commission from qualifying purchases on the links above. By using the links you help support this channel at no cost for you. #ai #rag #python #datascience #ThuVu

Original Description

Download Docker Desktop ๐Ÿ‘‰ https://dockr.ly/4e7k8tQ Containerize your generative AI application ๐Ÿ‘‰ https://dockr.ly/3TsIndW Github repo: ๐Ÿ‘‰ https://github.com/thu-vu92/structured-rag-pdf.git Master Python for AI Projects ๐Ÿ‘‰ https://python-course-earlybird.framer.website/?&utm_source=pdf2dataai Get regular data science/ AI content in your inbox: https://thu-vu.ck.page/49c5ee08f6 ๐Ÿ”‘ TIMESTAMPS โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€ 0:00 - Introduction to RAG 1:03 - Video outline 2:18 - Why RAG is useful 5:05 - Setting up project & Get API key 10:48 - Define LLM 12:16 - Process PDF document 13:43 - Split document 17:11 - Create text embeddings 20:18 - Vector database 23:43 - Query database 24:32 - Generate response 28:49 - Create Streamlit app 29:36 - Deploy app with Docker ๐Ÿ‘ฉ๐Ÿปโ€๐Ÿ’ป COURSES & RESOURCES โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€โ–€ ๐Ÿ“– Google Advanced Data Analytics Certificate ๐Ÿ‘‰ https://imp.i384100.net/anK9zZ ๐Ÿ“– Google Data Analytics Certificate ๐Ÿ‘‰ https://imp.i384100.net/15v9y6 ๐Ÿ“– Learn SQL Basics for Data Science Specialization ๐Ÿ‘‰ https://imp.i384100.net/AovPnJ ๐Ÿ“– Excel Skills for Business ๐Ÿ‘‰ https://coursera.pxf.io/doPaoy ๐Ÿ“– Machine Learning Specialization ๐Ÿ‘‰ https://imp.i384100.net/RyjykN ๐Ÿ“– Data Visualization with Tableau Specialization ๐Ÿ‘‰https://imp.i384100.net/n15XWR ๐Ÿ“– Deep Learning Specialization ๐Ÿ‘‰ https://imp.i384100.net/zavBA0 ๐Ÿ“– Mathematics for Machine Learning and Data Science Specialization ๐Ÿ‘‰ https://imp.i384100.net/LXK0gj ๐Ÿ“– Applied Data Science with Python ๐Ÿ‘‰ https://imp.i384100.net/gbxOqv As a member of the Amazon and Coursera Affiliate Programs, I earn a commission from qualifying purchases on the links above. By using the links you help support this channel at no cost for you. #ai #rag #python #datascience #ThuVu
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Chapters (13)

Introduction to RAG
1:03 Video outline
2:18 Why RAG is useful
5:05 Setting up project & Get API key
10:48 Define LLM
12:16 Process PDF document
13:43 Split document
17:11 Create text embeddings
20:18 Vector database
23:43 Query database
24:32 Generate response
28:49 Create Streamlit app
29:36 Deploy app with Docker
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