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Data science and machine learning in R /

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Xehetasun bibliografikoak
Egile nagusia:	Thareja, Reema
Formatua:	Liburua
Hizkuntza:	ingelesa
Argitaratua:	Chennai : McGraw Hill, c2021.
Gaiak:	Data analytics
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Antzeko izenburuak

Data science and machine learning in R /
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Data science and machine learning in R /
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Data science and machine learning in R /
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Data science and machine learning in R /
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Data Science and Machine Learning in R/
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Data Science and Machine Learning Using Python /
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Data Science and Machine Learning Using Python/
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Data Structures Using C /
nork: THAREJA, REEMA
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Data Structures Using C /
nork: THAREJA, REEMA
Argitaratua: (2016)

Data Structures Using C /
nork: THAREJA, REEMA
Argitaratua: (2016)

Machine Learning Governance for Managers
nork: Lazzeri, Francesca, et al.
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Modern data science with R
nork: Baumer, Benjamin, Author
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Big data and analytics/
nork: Acharya Seema
Argitaratua: (2019)

Big data and analytics/
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Argitaratua: (2019)

Big data and analytics /
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Argitaratua: (2020)

Big data and analytics /
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Big data and analytics/
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Argitaratua: (2019)

Big data and analytics /
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Dirty Data Processing for Machine Learning
nork: Qi, Zhixin, et al.
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R for Data Science / Import, Tidy, Transform, Visualize, and Model Data :
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Linear Algebra, Data Science, and Machine Learning
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Argitaratua: (2025)

Data mining with R : learning with case studies/
nork: Torgo, Luis
Argitaratua: (2011)

Practical Data Science with R /
nork: Zumel,Nina
Argitaratua: (2018)

Practical Data Science with R
nork: Zumel,Nina
Argitaratua: (2018)

Machine Learning for Data Science Handbook Data Mining and Knowledge Discovery Handbook /
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Machine Learning in Data Science Using Python /
nork: Rao, R. Nageswara
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Machine Learning with R : Learn how to Use R to Apply Powerful Machine Learning Methods and Gain an Insight Into Real-world Applications /
nork: Lantz,Brett
Argitaratua: (2013)

Machine Learning with R Learn how to Use R to Apply Powerful Machine Learning Methods and Gain an Insight Into Real-world Applications
nork: Lantz,Brett
Argitaratua: (2013)

R for Data Science : Import, Tidy, Transform, Visualize, and Model Data /
nork: Wickham,Hadley
Argitaratua: (2023)

R for Data Science Import, Tidy, Transform, Visualize, and Model Data
nork: Wickham,Hadley
Argitaratua: (2023)

R for Data Science : import, tidy, transform, visualize, and midel data/
nork: Wickham, Hadley
Argitaratua: (2023)

Hands-On Data Science With R : techniques to perform data manipulation and mining to build smart analytical models using R /
nork: Lanzetta, Vitor Bianchi
Argitaratua: (2018)

Data minig:practical machine learning tools and techniques
nork: Witren, Ian H.
Argitaratua: (2006)

Data Analytics and Machine Learning Navigating the Big Data Landscape /
Argitaratua: (2024)

Machine Learning : Theory and Applications /
nork: Govindaraja,V
Argitaratua: (2013)

Machine Learning Theory and Applications
nork: Govindaraja,V
Argitaratua: (2013)

Data Science An Introduction to Statistics and Machine Learning /
nork: Plaue, Matthias
Argitaratua: (2023)

Data Science and Machine Learning 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11–13, 2023, Proceedings /
Argitaratua: (2024)

Machine Learning and Big Data Analytics 2nd International Conference on Machine Learning and Big Data Analytics-ICMLBDA, IIT Patna, India, March 2022 /
Argitaratua: (2023)