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Autor(en): 
  • Engy Fouda
  • Learn Data Science Using Python: A Quick-Start Guide 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  November 2024  
    Genre:  EDV / Informatik 
     
    ArtificialIntelligence / dataanalysis / DataAnalytics / DataScience / datavisualization / Datenbanken / Datenmanagement / Programmier- und Skriptsprachen, allgemein / python
    ISBN:  9798868809347 
    EAN-Code: 
    9798868809347 
    Verlag:  Apress 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 11 mm 
    Gewicht:  306 gr 
    Seiten:  196 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Harness the capabilities of Python and gain the expertise need to master data science techniques. This step-by-step book guides you through using Python to achieve tasks related to data cleaning, statistics, and visualization. You'll start by reviewing the foundational aspects of the data science process. This includes an extensive overview of research points and practical applications, such as the insightful analysis of presidential elections. The journey continues by navigating through installation procedures and providing valuable insights into Python, data types, typecasting, and essential libraries like Pandas and NumPy. You'll then delve into the captivating world of data visualization. Concepts such as scatter plots, histograms, and bubble charts come alive through detailed discussions and practical code examples, unraveling the complexities of creating compelling visualizations for enhanced data understanding. Statistical analysis, linear models, and advanced data preprocessing techniques are also discussed before moving on to preparing data for analysis, including renaming variables, variable rearrangement, and conditional statements. Finally, you'll be introduced to regression techniques, demystifying the intricacies of simple and multiple linear regression, as well as logistic regression. What You'll Learn Understand installation procedures and valuable insights into Python, data types, typecasting Examine the fundamental statistical analysis required in most data science and analytics reports Clean the most common data set problems Use linear progression for data prediction Who This Book Is For Data Analysts, data scientists, Python programmers, and software developers new to data science.

      



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