Computer Science: Computer Science eTextbooks

This book addresses data mining and business analytics using the open-source software R. It covers both theory and practical skills for analyzing large datasets and building models for prediction and classification. The book includes real-world examples, exercises, and additional data for readers to practice their skills. It's suitable for both graduate students and practitioners in various fields.

The updated text focuses on new web application attacks and defenses. It covers new technologies, attack techniques, and countermeasures, including remoting frameworks, HTML5, cross-domain integration, UI redress, framebusting, HTTP parameter pollution, and hybrid file attacks.

Contains real-world case studies and detailed code examples in Python. Extract data from APIs and web pages; prepare textual data for statistical analysis and machine learning; use machine learning for classification, topic modeling, and summarization; explain AI models and classification results; explore and visualize semantic similarities with word embeddings; identify customer sentiment in product reviews; and create a knowledge graph based on named entities and their relations.