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Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute...

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...
Graphics of Large Datasets: Visualizing a Million (Statistics and Computing)
Graphics of Large Datasets: Visualizing a Million (Statistics and Computing)
Graphics are great for exploring data, but how can they be used for looking at the large datasets that are commonplace to-day? This book shows how to look at ways of visualizing large datasets, whether large in numbers of cases or large in numbers of variables or large in both. Data visualization is useful for data cleaning, exploring data,...
Introducing Monte Carlo Methods with R (Use R)
Introducing Monte Carlo Methods with R (Use R)

Computational techniques based on simulation have now become an essential part of the statistician's toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and skills for simulation than to use simulation to solve statistical problems. Introducing...

Become a Python Data Analyst: Perform exploratory data analysis and gain insight into scientific computing using Python
Become a Python Data Analyst: Perform exploratory data analysis and gain insight into scientific computing using Python

Enhance your data analysis and predictive modeling skills using popular Python tools

Key Features

  • Cover all fundamental libraries for operation and manipulation of Python for data analysis
  • Implement real-world datasets to perform predictive analytics with Python
  • ...
Functional Python Programming: Discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads, 2nd Edition
Functional Python Programming: Discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads, 2nd Edition

Create succinct and expressive implementations with functional programming in Python

Key Features

  • Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance
  • Get familiar with complex concepts such as monads,...
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
  • ...
Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

Unsupervised Learning with R
Unsupervised Learning with R

Work with over 40 packages to draw inferences from complex datasets and find hidden patterns in raw unstructured data

About This Book

  • Unlock and discover how to tackle clusters of raw data through practical examples in R
  • Explore your data and create your own models from scratch
  • ...
Programming Spiders, Bots, and Aggregators in Java
Programming Spiders, Bots, and Aggregators in Java
The content and services available on the web continue to be accessed mostly through direct human control. But this is changing. Increasingly, users rely on automated agents that save them time and effort by programmatically retrieving content, performing complex interactions, and aggregating data from diverse sources. Programming Spiders,...
Web Security Testing Cookbook: Systematic Techniques to Find Problems Fast
Web Security Testing Cookbook: Systematic Techniques to Find Problems Fast
Among the tests you perform on web applications, security testing is perhaps the most important, yet it's often the most neglected. The recipes in the Web Security Testing Cookbook demonstrate how developers and testers can check for the most common web security issues, while conducting unit tests, regression tests, or exploratory tests. Unlike ad...
Think Stats
Think Stats

If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.

By working with a single case study throughout this...

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