Productive and efficient data science with Python : with modularizing, memory profiles, and parallel/GPU processing

Productive and efficient data science with Python with modularizing, memory profiles, and parallel/GPU processing

This book focuses on the Python-based tools and techniques to help you become highly productive at all aspects of typical data science stacks such as statistical analysis, visualization, model selection, and feature engineering. You'll review the inefficiencies and bottlenecks lurking in the da...

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Detalles Bibliográficos
Otros Autores: Sarkar, Tirthajyoti, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: New York, NY : Apress [2022]
Edición:[First edition]
Materias:
Python (Computer program language)
Data mining.
Machine learning.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009669535106719
Tabla de Contenidos:
  • Chapter 1: What is Productive and Efficient Data Science
  • Chapter 2: Better Programming Principles for Efficient Data Science
  • Chapter 3: How to Use Python Data Science Packages more Productively
  • Chapter 4: Writing Machine Learning Code More Productively
  • Chapter 5: Modular and Productive Deep Learning Code
  • Chapter 6: Build Your Own Machine Learning Estimator/Package
  • Chapter 7: Some Cool Utility Packages
  • Chapter 8: Testing the Machine Learning Code
  • Chapter 9: Memory and Timing Profiling
  • Chapter 10: Scalable Data Science
  • Chapter 11: Parallelized Data Science
  • Chapter 12: GPU-Based Data Science for High Productivity
  • Chapter 13: Other Useful Skills to Master
  • Chapter 14: Wrapping It Up.

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