Hands-On Data Science with Anaconda : Utilize the right mix of tools to create high-performance data science applications /

Mostrar otras versiones (2)

Review questions and exercises; Chapter 3: Data Basics; Sources of data; UCI machine learning; Introduction to the Python pandas package; Several ways to input data; Inputting data using R; Inputting data using Python; Introduction to the Quandl data delivery platform; Dealing with missing data; Dat...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Yan, Yuxing (Autor)
Otros Autores: Yan, James
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham : Packt Publishing, 2018.
Temas:
ANACONDA (Electronic resource)
Machine learning.
Information visualization.
Electronic data processing.
Apprentissage automatique.
Visualisation de l'information.
Programming & scripting languages: general.
Mathematical theory of computation.
Information architecture.
Database design & theory.
Computers > Machine Theory.
Computers > Programming Languages > Python.
Computers > Data Modeling & Design.
COMPUTERS > General.
Electronic data processing
Information visualization
Machine learning
Acceso en línea:Texto completo
Descripción
Sumario:Review questions and exercises; Chapter 3: Data Basics; Sources of data; UCI machine learning; Introduction to the Python pandas package; Several ways to input data; Inputting data using R; Inputting data using Python; Introduction to the Quandl data delivery platform; Dealing with missing data; Data sorting; Slicing and dicing datasets; Merging different datasets; Data output; Introduction to the cbsodata Python package; Introduction to the datadotworld Python package; Introduction to the haven and foreign R packages; Introduction to the dslabs R package; Generating Python datasets.
Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. You will learn different ways to retrieve data from various sources and different visualization tools packages available in Python, R, and Julia.
Notas:General issues for optimization problems.
Descripción Física:1 online resource (356 pages)
ISBN:9781788834735
1788834739

Ejemplares similares