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Show Notes
Data Science (John D. Kelleher)
- Amazon USA Store: https://www.amazon.com/dp/0262535432?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Data-Science-John-D-Kelleher.html
- Apple Books: https://books.apple.com/us/audiobook/the-kaggle-book-data-analysis-and-machine-learning/id1682069344?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Data+Science+John+D+Kelleher+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/0262535432/
#Decisionmakingfromdata #Dataintegrationinfrastructure #Machinelearninggeneralization #Privacypreservingcomputation #Ethicaldatascience #DataScience
Data Science is a concise nonfiction overview of the field by John D. Kelleher and Brendan Tierney, published in the MIT Press Essential Knowledge series. Rather than functioning as a programming manual or a catalog of algorithms, it explains what data science is for: improving decisions through disciplined analysis of data. The book places familiar applications, including recommendation systems, spam filtering, targeted advertising, and insurance pricing, within a broader account of how organizations collect, integrate, model, and act on information. It distinguishes data science from adjacent areas such as data mining and machine learning while showing why they are deeply connected. Its coverage moves from the history and foundations of the discipline to project stages, infrastructure, machine learning tasks, privacy, regulation, and ethics. This scope makes the book an orientation to the full practice rather than a narrow technical introduction. Its central concern is that useful patterns and predictions matter only when data, problem definition, evaluation, organizational context, and social consequences are addressed together.
- Amazon USA Store: https://www.amazon.com/dp/0262535432?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Data-Science-John-D-Kelleher.html
- Apple Books: https://books.apple.com/us/audiobook/the-kaggle-book-data-analysis-and-machine-learning/id1682069344?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Data+Science+John+D+Kelleher+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/0262535432/
#Decisionmakingfromdata #Dataintegrationinfrastructure #Machinelearninggeneralization #Privacypreservingcomputation #Ethicaldatascience #DataScience
Data Science is a concise nonfiction overview of the field by John D. Kelleher and Brendan Tierney, published in the MIT Press Essential Knowledge series. Rather than functioning as a programming manual or a catalog of algorithms, it explains what data science is for: improving decisions through disciplined analysis of data. The book places familiar applications, including recommendation systems, spam filtering, targeted advertising, and insurance pricing, within a broader account of how organizations collect, integrate, model, and act on information. It distinguishes data science from adjacent areas such as data mining and machine learning while showing why they are deeply connected. Its coverage moves from the history and foundations of the discipline to project stages, infrastructure, machine learning tasks, privacy, regulation, and ethics. This scope makes the book an orientation to the full practice rather than a narrow technical introduction. Its central concern is that useful patterns and predictions matter only when data, problem definition, evaluation, organizational context, and social consequences are addressed together.
