Python 3 and Machine Learning Using ChatGPT/GPT-4 / / Oswald Campesato.
This book is designed to bridge the gap between theoretical knowledge and practical application in the fields of Python programming, machine learning, and the innovative use of ChatGPT-4 in data science. The book is structured to facilitate a deep understanding of several core topics. It begins with...
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Place / Publishing House: | Dulles, VA : : Mercury Learning and Information, , [2024] ©2024 |
Year of Publication: | 2024 |
Language: | English |
Series: | MLI Generative AI Series
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Online Access: | |
Physical Description: | 1 online resource |
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LEADER | 03465nam a2200565 4500 | ||
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001 | 9781501520112 | ||
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100 | 1 | |a Campesato, Oswald, |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
245 | 1 | 0 | |a Python 3 and Machine Learning Using ChatGPT/GPT-4 / |c Oswald Campesato. |
264 | 1 | |a Dulles, VA : |b Mercury Learning and Information, |c [2024] | |
264 | 4 | |c ©2024 | |
300 | |a 1 online resource | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
347 | |a text file |b PDF |2 rda | ||
490 | 0 | |a MLI Generative AI Series | |
505 | 0 | 0 | |t Frontmatter -- |t Contents -- |t Preface -- |t Chapter 1: Introduction to Pandas -- |t Chapter 2: Introduction to Machine Learning -- |t Chapter 3: Classifiers in Machine Learning -- |t Chapter 4: ChatGPT and GPT-4 -- |t Chapter 5: Linear Regression with GPT-4 -- |t Chapter 6: Machine Learning Classifiers with GPT-4 -- |t Chapter 7: Machine Learning Clustering with GPT-4 -- |t Chapter 8: ChatGPT and Data Visualization -- |t Index |
506 | 0 | |a restricted access |u http://purl.org/coar/access_right/c_16ec |f online access with authorization |2 star | |
520 | |a This book is designed to bridge the gap between theoretical knowledge and practical application in the fields of Python programming, machine learning, and the innovative use of ChatGPT-4 in data science. The book is structured to facilitate a deep understanding of several core topics. It begins with a detailed introduction to Pandas, a cornerstone Python library for data manipulation and analysis. Next, it explores a variety of machine learning classifiers from kNN to SVMs. In later chapters, it discusses the capabilities of GPT-4, and how its application enhances traditional linear regression analysis. Finally, the book covers the innovative use of ChatGPT in data visualization. This segment focuses on how AI can transform data into compelling visual stories, making complex results accessible and understandable. It includes material on AI apps, GANs, and DALL-E. Companion files are available for downloading with code and figures from the text. | ||
530 | |a Issued also in print. | ||
538 | |a Mode of access: Internet via World Wide Web. | ||
546 | |a In English. | ||
588 | 0 | |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 03. Jul 2024) | |
650 | 7 | |a COMPUTERS / Programming / Open Source. |2 bisacsh | |
653 | |a Python, Machine Learning, ChatGPT-4, Pandas, Classifiers, Linear Regression, Data Visualization, AI, Data Science, Programming. | ||
776 | 0 | |c EPUB |z 9781501520174 | |
776 | 0 | |c print |z 9781501522956 | |
856 | 4 | 0 | |u https://doi.org/10.1515/9781501520112 |
856 | 4 | 0 | |u https://www.degruyter.com/isbn/9781501520112 |
856 | 4 | 2 | |3 Cover |u https://www.degruyter.com/document/cover/isbn/9781501520112/original |
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