Python Data Analysis
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
MATLAB Control Systems Engineering
MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or...
Practical Data Analysis
Transform, model, and visualize your data through hands-on projects, developed in open source tools
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
Visual Saliency: From Pixel-Level to Object-Level Analysis
This book provides an introduction to recent advances in theory, algorithms and application of Boolean map distance for image processing. Applications include modeling what humans find salient or prominent in an image, and then using this for guiding smart image cropping, selective image filtering, image segmentation, image matting, etc....
Virtual Reality: Second International Conference, ICVR 2007, Held as Part of HCI International 2007, Beijing, China, July 22-27, 2007, Proceedings This book constitutes the refereed proceedings of the Second International Conference on Virtual Reality, ICVR 2007, held in Beijing, China in July 2007 in the framework of the 12th International Conference on Human-Computer Interaction, HCII 2007 with 8 other thematically similar conferences.
The 81 revised papers presented were carefully...
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...
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