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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...
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...
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...
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...
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...
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...
A Beginner's Guide to R (Use R!)
A Beginner's Guide to R (Use R!)

Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum.

...
Analyzing Baseball Data with R (Chapman & Hall/CRC The R Series)
Analyzing Baseball Data with R (Chapman & Hall/CRC The R Series)

With its flexible capabilities and open-source platform, R has become a major tool for analyzing detailed, high-quality baseball data. Analyzing Baseball Data with R provides an introduction to R for sabermetricians, baseball enthusiasts, and students interested in exploring the rich sources of baseball data. It...

R Reference Manual: Base Package, Vol. 1
R Reference Manual: Base Package, Vol. 1
This manual is the first volume of the reference documentation for R, a powerful free environment for statistical computing and graphics. The main commands of the base package of R are described in this volume. A second companion volume "The R Reference Manual - Base Package - Volume 2" (ISBN 0-9546120-1-9) covers the R commands for...
MATLAB® and Design Recipes for Earth Sciences: How to Collect, Process and Present Geoscientific Information
MATLAB® and Design Recipes for Earth Sciences: How to Collect, Process and Present Geoscientific Information

The overall aim of the book is to introduce students to the typical course followed by a data analysis project in earth sciences. A project usually involves searching relevant literature, reviewing and ranking published books and journal articles, extracting relevant information from the literature in the form of text, data, or...

Reproducible Research with R and R Studio (Chapman & Hall/CRC The R Series)
Reproducible Research with R and R Studio (Chapman & Hall/CRC The R Series)

Bringing together computational research tools in one accessible source, Reproducible Research with R and RStudio guides you in creating dynamic and highly reproducible research. Suitable for researchers in any quantitative empirical discipline, it presents practical tools for data collection, data analysis, and the...

Modern Analysis of Customer Surveys: with Applications using R
Modern Analysis of Customer Surveys: with Applications using R
Customer survey studies deals with customers, consumers and user satisfaction from a product or service. In practice, many of the customer surveys conducted by business and industry are analyzed in a very simple way, without using models or statistical methods. Typical reports include descriptive statistics and basic graphical displays. As...
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