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Beginning Data Science with Python and Jupyter: Use powerful tools to unlock actionable insights from data
Beginning Data Science with Python and Jupyter: Use powerful tools to unlock actionable insights from data

Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction.

Key Features

  • Get up and running with the Jupyter ecosystem and some example datasets
  • ...
PySpark SQL Recipes: With HiveQL, Dataframe and Graphframes
PySpark SQL Recipes: With HiveQL, Dataframe and Graphframes
Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using graphframes and see how to...
Network Security Through Data Analysis: Building Situational Awareness
Network Security Through Data Analysis: Building Situational Awareness

Traditional intrusion detection and logfile analysis are no longer enough to protect today’s complex networks. In this practical guide, security researcher Michael Collins shows you several techniques and tools for collecting and analyzing network traffic datasets. You’ll understand how your network is used, and what...

Python Data Analysis
Python Data Analysis

Key Features

  • Find, manipulate, and analyze your data using the Python 3.5 libraries
  • Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code
  • An easy-to-follow guide with realistic examples that are frequently used in real-world data...
Big Data Analysis with Python: Combine Spark and Python to unlock the powers of parallel computing and machine learning
Big Data Analysis with Python: Combine Spark and Python to unlock the powers of parallel computing and machine learning

Get to grips with processing large volumes of data and presenting it as engaging, interactive insights using Spark and Python.

Key Features

  • Get a hands-on, fast-paced introduction to the Python data science stack
  • Explore ways to create useful metrics and statistics from...
Applied Data Science with Python and Jupyter: Use powerful industry-standard tools to unlock new, actionable insights from your data
Applied Data Science with Python and Jupyter: Use powerful industry-standard tools to unlock new, actionable insights from your data

Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications.

Key Features

  • Get up and running with the Jupyter ecosystem and some example datasets
  • Learn about key machine...
Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation
Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation
This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and...
Learn RStudio IDE: Quick, Effective, and Productive Data Science
Learn RStudio IDE: Quick, Effective, and Productive Data Science
Discover how to use the popular RStudio IDE as a professional tool that includes code refactoring support, debugging, and Git version control integration. This book gives you a tour of RStudio and shows you how it helps you do exploratory data analysis; build data visualizations with ggplot; and create custom R packages and...
Matplotlib 3.0 Cookbook: Over 150 recipes to create highly detailed interactive visualizations using Python
Matplotlib 3.0 Cookbook: Over 150 recipes to create highly detailed interactive visualizations using Python

Build attractive, insightful, and powerful visualizations to gain quality insights from your data

Key Features

  • Master Matplotlib for data visualization
  • Customize basic plots to make and deploy figures in cloud environments
  • Explore recipes to design various...
Statistical Methods in Analytical Chemistry (Chemical Analysis: A Series of Monographs on Analytical Chemistry and Its Applications)
Statistical Methods in Analytical Chemistry (Chemical Analysis: A Series of Monographs on Analytical Chemistry and Its Applications)

This new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments. Complete with examples from the chemical and pharmaceutical laboratory and manufacturing areas, this thoroughly updated book clearly...

Practical Data Analysis
Practical Data Analysis

Transform, model, and visualize your data through hands-on projects, developed in open source tools

Overview

  • Explore how to analyze your data in various innovative ways and turn them into insight
  • Learn to use the D3.js visualization tool for exploratory data analysis
  • ...
Data Mining for Geoinformatics: Methods and Applications
Data Mining for Geoinformatics: Methods and Applications

The rate at which geospatial data is being generated exceeds our computational capabilities to extract patterns for the understanding of a dynamically changing world. Geoinformatics and data mining focuses on the development and implementation of computational algorithms to solve these problems. This unique volume contains a collection of...

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