Data Science and Analytics with Python

von

Rogel-Salazar, Jesus

BuchKartoniert, Paperback

Verkaufsrang52106inInformatik EDV

CHF83.90

BuchabCHF78.90

E-BookabCHF92.85

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Beschreibung

The book is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main concepts used in data analytics using tools developed in Python, such as SciKit Learn, Pandas, Numpy, etc.

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ISBN/GTIN978-1-4987-4209-2

ProduktartBuch

EinbandKartoniert, Paperback

VerlagTaylor and FrancisChapman and Hall/CRC

Erscheinungsdatum16.08.2017

Auflage1. A.

ReiheChapman & Hall/CRC Data Mining and Knowledge Discovery Series

Seiten412 Seiten

SpracheEnglisch

MasseBreite 191 mm, Höhe 235 mm

Gewicht746 g

IllustrationenFarb., s/w. Abb.

Artikel-Nr.22170057

KatalogBuchzentrum

Datenquelle-Nr.22291160

WarengruppeInformatik EDV

Weitere Details

Reihe

Social Computing

Knowledge-Driven Medicine

Spatial and Spatiotemporal Data Mining

Automated Data Analysis Using Excel

Understanding Complex Datasets

Computational Methods of Feature Selection

Multimedia Data Mining

Knowledge Discovery for Counterterrorism and Law Enforcement

Constrained Clustering

Data Mining for Design and Marketing

Biological Data Mining

The Top Ten Algorithms in Data Mining

Text Mining

Information Discovery on Electronic Health Records

Geographic Data Mining and Knowledge Discovery

Statistical Data Mining Using SAS Applications

Knowledge Discovery from Data Streams

Handbook of Educational Data Mining

Music Data Mining

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Mining Software Specifications

Spectral Feature Selection for Data Mining

Advances in Machine Learning and Data Mining for Astronomy

Contrast Data Mining

Support Vector Machines

Computational Business Analytics

RapidMiner

Computational Intelligent Data Analysis for Sustainable Development

Data Clustering

Data Classification

Accelerating Discovery

Event Mining

Graph-Based Social Media Analysis

Healthcare Data Analytics

Text Mining and Visualization

Advances in Machine Learning and Data Mining for Astronomy

Data Mining for Design and Marketing

Mining Software Specifications

Biological Data Mining

Data Science and Analytics with Python

Social Networks with Rich Edge Semantics

Large-Scale Machine Learning in the Earth Sciences

Data Mining with R

Spectral Feature Selection for Data Mining

Feature Engineering for Machine Learning and Data Analytics

Human Capital Systems, Analytics, and Data Mining

Exploratory Data Analysis Using R

Industrial Applications of Machine Learning

Exploratory Data Analysis Using R

Data Analytics

Automated Data Analysis Using Excel

Mobility Data Modeling and Analysis

Knowledge Guided Machine Learning

Data Science and Machine Learning for Non-Programmers

Knowledge Guided Machine Learning

Data Science and Analytics with Python

RapidMiner, Second Edition

Data Science and Machine Learning for Non-Programmers

Über den/die AutorIn

Rogel-Salazar, Jesus

Dr. Jesús Rogel-Salazar is a Lead Data Scientist at IBM Data Science Studio and visiting researcher at the Department of Physics at Imperial College London, UK. He is also a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK. He obtained his doctorate in Physics at Imperial College London for work on quantum atom optics and ultra-cold matter. He has held a position as senior lecturer in mathematics as well as a consultant and data scientist in the financial industry since 2006. He is the author of the book "Essential Matlab and Octave", also published with CRC Press. His interests include mathematical modelling, data science and optimisation in a wide range of applications including optics, quantum mechanics, data journalism and finance. Dr. Jesús Rogel-Salazar is a Lead Data Scientist at IBM Data Science Studio and visiting researcher at the Department of Physics at Imperial College London, UK. He is also a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK. He obtained his doctorate in Physics at Imperial College London for work on quantum atom optics and ultra-cold matter. He has held a position as senior lecturer in mathematics as well as a consultant and data scientist in the financial industry since 2006. He is the author of the book "Essential Matlab and Octave", also published with CRC Press. His interests include mathematical modelling, data science and optimisation in a wide range of applications including optics, quantum mechanics, data journalism and finance.

Data Science and Analytics with Python

Beschreibung

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