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E-BooksData Analysis with LLMs Text, tables, images and sound (In Action)



Data Analysis with LLMs Text, tables, images and sound (In Action)
Free Download Data Analysis with LLMs
by Immanuel Trummer

English | 2025 | ISBN: 1633437647 | 232 pages | True/Retail EPUB | 13.53 MB


Speed up common data science tasks with AI assistants like ChatGPT and Large Language Models (LLMs) from Anthropic, Cohere, Open AI, Google, Hugging Face, and more!
Data Analysis with LLMsteaches you to use the new generation of AI assistants and Large Language Models (LLMs) to aid and accelerate common data science tasks.
Learn how to use LLMs to:
Analyze text, tables, images, and audio filesExtract information from multi-modal data lakesClassify, cluster, transform, and query multimodal dataBuild natural language query interfaces over structured data sourcesUse LangChain to build complex data analysis pipelinesPrompt engineering and model configuration
All practical,Data Analysis with LLMstakes you from your first prompts through advanced techniques like creating LLM-based agents for data analysis and fine-tuning existing models. You'll learn how to extract data, build natural language query interfaces, and much more.
About the technology
Large Language Models (LLMs) can streamline and accelerate almost any data science task. Master the techniques in this book, and you'll be able to analyze large amounts of text, tabular and graph data, images, videos, and more with clear natural language prompts and a few lines of Python code.
About the book
Data Analysis with LLMsshows you exactly how to integrate generative AI into your day-to-day work as a data scientist. In it, Cornell professor Immanuel Trummer guides you through a series of engaging projects that introduce OpenAI's Python library, tools like LangChain and LlamaIndex, and LLMs from Anthropic, Cohere, and Hugging Face. As you go, you'll use AI to query structured and unstructured data, analyze sound and images, and optimize the cost and quality of your data analysis process.
What's insideClassify, cluster, transform, and query multimodal dataBuild natural language query interfaces over structured data sourcesCreate LLM-based agents for autonomous data analysisPrompt engineering and model configuration
About the reader
For data scientists and data analysts who know the basics of Python.
About the author
Immanuel Trummeris an associate professor of computer science at Cornell University and a member of the Cornell Database Group.
Table of Contents
Part 1
1 Analyzing data with large language models
2 Chatting with ChatGPT
Part 2
3 The OpenAI Python library
4 Analyzing text data
5 Analyzing structured data
6 Analyzing images and videos
7 Analyzing audio data
Part 3
8 GPT alternatives
9 Optimizing cost and quality
10 Software frameworks



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