Titlebook: Data Science Solutions with Python; Fast and Scalable Mo Tshepo Chris Nokeri Book 2022 Tshepo Chris Nokeri 2022 Big Data Analytics.Machine

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Initiative

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里程碑

Teruyo Wada,Masao Ikeda,Eiho UezatoThis chapter executes and assesses nonlinear neural networks to address binary classification using a diverse set of comprehensive Python frameworks (i.e., Scikit-Learn, Keras, and H2O).

incubus

Judicious

https://doi.org/10.1007/978-1-4684-1605-3This chapter executes a simple dimension reducer (a principal component method) by implementing a diverse set of Python frameworks (Scikit-Learn, PySpark, and H2O). To begin, it clarifies how the method computes components.

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AGGER

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Survival Analysis withPySpark and Lifelines,This chapter describes and executes several survival analysis methods using the main Python frameworks (i.e., Lifelines and PySpark). It begins by explaining the underlying concept behind the Cox Proportional Hazards model. It then introduces the accelerated failure time method.