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Show Notes
Data Science from Scratch: First Principles with Python (Joel Grus)
- Amazon USA Store: https://www.amazon.com/dp/1492041130?tag=9natree-20
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- Read more: https://english.9natree.com/read/1492041130/
#Algorithmimplementation #Statisticalinference #Pythondataworkflows #Supervisedandunsupervisedlearning #Naturallanguageprocessing #DataSciencefromScratch
Data Science from Scratch: First Principles with Python is a technical introduction to data science by software engineer and former data scientist Joel Grus. The 2019 second edition uses Python 3 and approaches the field through implementation rather than through immediate reliance on mature data science packages. Its central purpose is to make common methods intelligible by rebuilding simplified versions of the mathematical tools, data workflows, and machine learning algorithms that practitioners often encounter as library calls. The book begins with a compact Python orientation and develops the linear algebra, probability, and statistics needed for later chapters. It then moves across data acquisition and cleaning, visualization, inference, supervised and unsupervised learning, neural networks, recommender systems, natural language processing, network analysis, MapReduce, and databases. This breadth makes it closer to a guided survey of foundational computational ideas than to a narrowly focused machine learning manual. Grus emphasizes conceptual transparency, while accepting that the implementations are educational versions rather than production systems optimized for scale, reliability, or contemporary software ecosystems.
- Amazon USA Store: https://www.amazon.com/dp/1492041130?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Data-Science-from-Scratch%3A-First-Principles-with-Python-Joel-Grus.html
- eBay: https://www.ebay.com/sch/i.html?_nkw=Data+Science+from+Scratch+First+Principles+with+Python+Joel+Grus+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/1492041130/
#Algorithmimplementation #Statisticalinference #Pythondataworkflows #Supervisedandunsupervisedlearning #Naturallanguageprocessing #DataSciencefromScratch
Data Science from Scratch: First Principles with Python is a technical introduction to data science by software engineer and former data scientist Joel Grus. The 2019 second edition uses Python 3 and approaches the field through implementation rather than through immediate reliance on mature data science packages. Its central purpose is to make common methods intelligible by rebuilding simplified versions of the mathematical tools, data workflows, and machine learning algorithms that practitioners often encounter as library calls. The book begins with a compact Python orientation and develops the linear algebra, probability, and statistics needed for later chapters. It then moves across data acquisition and cleaning, visualization, inference, supervised and unsupervised learning, neural networks, recommender systems, natural language processing, network analysis, MapReduce, and databases. This breadth makes it closer to a guided survey of foundational computational ideas than to a narrowly focused machine learning manual. Grus emphasizes conceptual transparency, while accepting that the implementations are educational versions rather than production systems optimized for scale, reliability, or contemporary software ecosystems.
