Thinking Data Science A Data Science Practitioner’s Guide /

This definitive guide to Machine Learning projects answers the problems an aspiring or experienced data scientist frequently has: Confused on what technology to use for your ML development? Should I use GOFAI, ANN/DNN or Transfer Learning? Can I rely on AutoML for model development? What if the clie...

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Bibliográfalaš dieđut
Váldodahkki: Sarang, Poornachandra (Dahkki)
Searvvušdahkki: SpringerLink (Online service)
Materiálatiipa: Elektrovnnalaš E-girji
Giella:eaŋgalasgiella
Almmustuhtton: Cham : Springer International Publishing : Imprint: Springer, 2023.
Preanttus:1st ed. 2023.
Ráidu:The Springer Series in Applied Machine Learning,
Fáttát:
Liŋkkat:https://doi.org/10.1007/978-3-031-02363-7
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