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Practical Data Mining
Practical Data Mining

Used by corporations, industry, and government to inform and fuel everything from focused advertising to homeland security, data mining can be a very useful tool across a wide range of applications. Unfortunately, most books on the subject are designed for the computer scientist and statistical illuminati and leave the reader largely...

Forest Analytics with R: An Introduction (Use R!)
Forest Analytics with R: An Introduction (Use R!)
R is an open-source and free software environment for statistical computing and graphics. R compiles and runs on a wide variety of UNIX platforms (e.g., GNU/Linux and FreeBSD), Windows, and Mac OSX. Since the late 1990s, R has been developed by hundreds of contributors and new capabilities are added each month....
Randomized Algorithms for Analysis and Control of Uncertain Systems: With Applications (Communications and Control Engineering)
Randomized Algorithms for Analysis and Control of Uncertain Systems: With Applications (Communications and Control Engineering)

The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of...

Jupyter Cookbook: Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more
Jupyter Cookbook: Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

Leverage the power of the popular Jupyter notebooks to simplify your data science tasks without any hassle

Key Features

  • Create and share interactive documents with live code, text and visualizations
  • Integrate popular programming languages such as Python, R, Julia, Scala...
Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition
Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition

Build a strong foundation of machine learning algorithms in 7 days

Key Features

  • Use Python and its wide array of machine learning libraries to build predictive models
  • Learn the basics of the 7 most widely used machine learning algorithms within a week
  • Know...
Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data
Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data

Understand, explore, and effectively present data using the powerful data visualization techniques of Python

Key Features

  • Use the power of Pandas and Matplotlib to easily solve data mining issues
  • Understand the basics of statistics to build powerful predictive data...
Hands-On Neural Networks with Keras: Design and create neural networks using deep learning and artificial intelligence principles
Hands-On Neural Networks with Keras: Design and create neural networks using deep learning and artificial intelligence principles

Your one-stop guide to learning and implementing artificial neural networks with Keras effectively

Key Features

  • Design and create neural network architectures on different domains using Keras
  • Integrate neural network models in your applications using this highly practical...
Applied Data Visualization with R and ggplot2: Create useful, elaborate, and visually appealing plots
Applied Data Visualization with R and ggplot2: Create useful, elaborate, and visually appealing plots

Develop informative and aesthetic visualizations that enable effective data analysis in less time

Key Features

  • Discover structure of ggplot2, grammar of graphics, and geometric objects
  • Study how to design and implement visualization from scratch
  • Explore...
R Deep Learning Projects: Master the techniques to design and develop neural network models in R
R Deep Learning Projects: Master the techniques to design and develop neural network models in R

5 real-world projects to help you master deep learning concepts

Key Features

  • Master the different deep learning paradigms and build real-world projects related to text generation, sentiment analysis, fraud detection, and more
  • Get to grips with R's impressive range of...
Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python
Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python

Develop real-world applications powered by the latest advances in intelligent systems

Key Features

  • Gain real-world contextualization using deep learning problems concerning research and application
  • Get to know the best practices to improve and optimize your machine...
Internet of Things for Architects: Architecting IoT solutions by implementing sensors, communication infrastructure, edge computing, analytics, and security
Internet of Things for Architects: Architecting IoT solutions by implementing sensors, communication infrastructure, edge computing, analytics, and security

Learn to design, implement and secure your IoT infrastructure

Key Features

  • Build a complete IoT system that is the best fit for your organization
  • Learn about different concepts, technologies, and tradeoffs in the IoT architectural stack
  • Understand the...
ggplot2: Elegant Graphics for Data Analysis (Use R!)
ggplot2: Elegant Graphics for Data Analysis (Use R!)
ggplot2 is an R package for producing statistical, or data, graphics, but it is unlike most other graphics packages because it has a deep underlying grammar. This grammar, based on the Grammar of Graphics (Wilkinson, 2005), is composed of a set of independent components that can be composed in many different...
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