{"product_id":"data-analysis-with-llms","title":"Data Analysis with LLMs","description":"\u003cp\u003e\u003cb\u003eSpeed 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!\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eData Analysis with LLMs\u003c\/i\u003e teaches you to use the new generation of AI assistants and Large Language Models (LLMs) to aid and accelerate common data science tasks.\u003c\/p\u003e\u003cp\u003eLearn how to use LLMs to:\u003c\/p\u003e\u003cp\u003e• Analyze text, tables, images, and audio files\u003cbr\u003e• Extract information from multi-modal data lakes\u003cbr\u003e• Classify, cluster, transform, and query multimodal data\u003cbr\u003e• Build natural language query interfaces over structured data sources\u003cbr\u003e• Use LangChain to build complex data analysis pipelines\u003cbr\u003e• Prompt engineering and model configuration\u003c\/p\u003e\u003cp\u003eAll practical, \u003ci\u003eData Analysis with LLMs\u003c\/i\u003e takes 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.\u003c\/p\u003e\u003cp\u003ePurchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout the technology\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eLarge 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.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout the book\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003ci\u003eData Analysis with LLMs\u003c\/i\u003e shows 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.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eWhat's inside\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e• Classify, cluster, transform, and query multimodal data\u003cbr\u003e• Build natural language query interfaces over structured data sources\u003cbr\u003e• Create LLM-based agents for autonomous data analysis\u003cbr\u003e• Prompt engineering and model configuration\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout the reader\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eFor data scientists and data analysts who know the basics of Python.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAbout the author\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eImmanuel Trummer\u003c\/b\u003e is an associate professor of computer science at Cornell University and a member of the Cornell Database Group.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003ePart 1\u003cbr\u003e1 Analyzing data with large language models\u003cbr\u003e2 Chatting with ChatGPT\u003cbr\u003ePart 2\u003cbr\u003e3 The OpenAI Python library\u003cbr\u003e4 Analyzing text data\u003cbr\u003e5 Analyzing structured data\u003cbr\u003e6 Analyzing images and videos\u003cbr\u003e7 Analyzing audio data\u003cbr\u003ePart 3\u003cbr\u003e8 GPT alternatives\u003cbr\u003e9 Optimizing cost and quality\u003cbr\u003e10 Software frameworks\u003c\/p\u003e\u003cp\u003e\u003cspan style=\"color: rgb(34, 34, 34); font-size: 24px; font-weight: 700;\"\u003eAbout the Author\u003c\/span\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eImmanuel Trummer\u003c\/b\u003e is an assistant professor for computer science at Cornell University and leader of the Cornell Database Group. His papers have been selected for “Best of VLDB”, “Best of SIGMOD”, for the ACM SIGMOD Research Highlight Award, and for publication in CACM as CACM Research Highlight. Immanuel’s online course on data management has reached over a million views on YouTube. Over the past few years, his group has published extensively on projects that apply large language models in the context of data science.\u003c\/p\u003e\u003cp\u003e\u003cb\u003e\u003cbr\u003e\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eEbook License\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eEnd-User Warranty And License Agreement\u003c\/p\u003e\u003cp\u003e1. Grant Of License\u003c\/p\u003e\u003cp\u003eManning Has Authorized The Download By You Of An Unrestricted Number Of Copies Of The Electronic Book (Ebook) In Any Of The Available Formats. Manning Grants You A Nonexclusive, Nontransferable License To Use The Ebook According To The Terms And Conditions Herein. This License Agreement Permits You To Install The Ebook On Any And All Your Devices For Your Personal Use Only.\u003c\/p\u003e\u003cp\u003e2. Restrictions\u003c\/p\u003e\u003cp\u003eYou Shall Not: (1) Share, Resell, Rent, Assign, Timeshare, Distribute, Or Transfer All Or Part Of The Ebook Or Any Rights Granted Hereunder To Any Other Person; (2) Duplicate The Ebook, Except For A Single Backup Or Archival Copy; (3) Remove Any Proprietary Notices, Labels, Or Marks From The Ebook; (4) Transfer Or Sublicense Title To The Ebook To Any Other Party.\u003c\/p\u003e\u003cp\u003e3. Intellectual Property Protection\u003c\/p\u003e\u003cp\u003eThe Ebook Is Owned By Manning And Is Protected By United States And International Copyright And Other Intellectual Property Laws. Manning Reserves All Rights In The Ebook Not Expressly Granted Herein. This License And Your Right To Use The Ebook Terminate Automatically If You Violate Any Part Of This Agreement. In The Event Of Termination, You Must Remove The Original And Any Copies Of The Ebook From All Your Devices.\u003c\/p\u003e\u003cp\u003e4. Source Code Supplementary Material\u003c\/p\u003e\u003cp\u003eAny Source Code Files Provided As A Supplement To The Book Are Freely Available To The Public For Download. Reuse Of The Code Is Permitted, In Whole Or In Part, Including The Creation Of Derivative Works, Provided That You Acknowledge That You Are Using It And Identify The Source: Title, Publisher And Year.\u003c\/p\u003e\u003cp\u003e5. Limited Warranty\u003c\/p\u003e\u003cp\u003eManning Warrants That The Ebook Files, A Copy Of Which You Are Authorized To Download, Are Free From Defects In The Operational Sense That They Can Be Read By A Pdf Reader Or Epub Reader, Or Other. 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