Learn the fundamentals of Python (3.7) and how to apply it to data science, programming, and web development. Fully updated to include hands-on tutorials and projects.
Key Features
Learn the fundamentals of Python programming with interactive projects
Wireless mesh networks (WMNs) have recently received a great deal of attention as a
promising cost-effective solution to provide coverage and broadband wireless
connectivity for mobile users to get access to different IP applications and services.
The factor that has helped WMNs become attractive is the wide application prospects...
Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.
This revision is fully updated with new content on social media data analysis, image...
Dive Into Algorithms is a broad introduction to algorithms using the Python Programming Language.
Dive Into Algorithms is a wide-ranging, Pythonic tour of many of the world's most interesting algorithms. With little more than a bit of computer programming experience and basic high-school math,...
As business priorities change and focus shifts to address arising issues, HR professionals need to be able to reorganize talent swiftly and plan for future needs to enable the business to succeed. It covers how to forecast organizational demand for people, resources and skills, analyze the gap between supply and demand and most...
Master the syntax for working with R’s plotting functions in graphics and stats in this easy reference to formatting plots. The approach in Visualizing Data in R 4 toward the application of formatting in ggplot() will follow the structure of the formatting used by the plotting functions in graphics and...
Nearly all the computers sold today have a multi-core processor, but only a small number of applications are written to take advantage of the extra cores. Most programmers are playing catch-up. A recent consultation with a group of senior programming engineers revealed the top three hurdles in adopting parallelism: the challenges of porting...
This book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods. It also exhibits the tools which make it possible to assess the predictive performance of tree-based models. Actuaries need these advanced analytical tools to turn the massive data sets now at their...
