The Data Mine’s Bookshelf
This page is still under construction. For now, you might find short hand names of the books. We are working on listing all the Purdue library links here. If you look up any of these books on Purdue’s library (which anyone can do, even non Purdue students) you will almost certainly find the book. |
While most of these books are scattered throughout the Starter Guides on their respective topics, they are also listed here under their approximate content domain. All of these books come highly recommended. For Purdue students, most if not all of these books are free at the Purdue library link; for non-Purdue students, a good chunk of them should be free.
Data Analysis
Visualization
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Maps for advocacy
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Seeing with fresh eyes
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Visualizing data (both of them)
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Visualizing information for advocacy
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S plus trellis graphics
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Interactive Data Visualization for the web
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Learning Microsoft Power BI
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Fundamentals of data visualization
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Presenting to win
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The atlas of the real world
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Making Data Visual
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Tableau Desktop Cookbook by Lorna Brown (O’Reilly, 2021)
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Innovative Tableau by Ryan Sleeper (O’Reilly, 2020)
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Practical Tableau by Ryan Sleeper (O’Reilly, 2018)
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Communicating Data with Tableau by Ben Jones (O’Reilly, 2014)
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Tableau Strategies by Ann Jackson and Luke Stanke (O’Reilly, 2021)
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Tableau Prep: Up & Running by Carl Allchin (O’Reilly, 2020)
Analysis Techniques
Machine Learning
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Machine Learning for Hackers
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The Elements of stat learning
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Intro to Statistical Learning, 2nd edition
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Hands on Machine Learning
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Machine Learning
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Machine learning design patterns
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AI + ML for coders
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Building Machine Learning powered apps
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Real world machine learning
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Building machine learning pipelines
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Reinforcement Learning
NLP
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Natural Language Processing with Transformers by Lewis Tunstall, Leandro von Werra, and Thomas Wolf (O’Reilly, 2022)
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Practical Natural Language Processing by Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana (O’Reilly, 2020)
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Natural Language Processing with PyTorch by Delip Rao and Brian McMahan (O’Reilly, 2019)
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GPT-3 by Sandra Kublik and Shubham Saboo (O’Reilly, 2022)
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Natural Language Processing with Spark NLP by Alex Thomas (O’Reilly, 2020)
General
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97 Things every cloud engineer should know
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97 things data engineer
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Foundations for architecting data solutions
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Building secure and reliable systems
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Designing Data Intensive Applications
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97 things every engineering manager should know
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The enterprise big data lake
Platforms
Agile
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Agile Data Science 2.0
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Agile for everybody
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97 things every scrum
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Learning agile
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Agile project management
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Agile practice guide
Incorporating Diverse Backgrounds
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Asked and Answered by Pamela E. Harris and Aris Winger (2020)
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Practices and Policies by Pamela E. Harris and Aris Winger (2021)
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Read and Rectify by Pamela E. Harris and Aris Winger (2022)
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Testimonios by Pamela E. Harris, Alicia Prieto-Langarica, Vanessa Rivera Quiñones, Luis Sordo Vieira, Rosaura Uscanga, and Andrés R. Vindas Meléndez
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Unleash Different by Rich Donovan (2018)