Результати пошуку
Hemang Doshi, Javen Khoo Ai Wee
Following on from the success of its bestselling predecessor, this third edition of the CISA - Certified Information Systems Auditor Study Guide serves as your go-to resource for acing the CISA exam. Written by renowned CISA expert Hemang Doshi, this guide equips you with practical skills and in-depth knowledge to excel in information systems auditing, setting the foundation for a thriving career.Fully updated to align with the 28th edition of the CISA Official Review Manual, this guide covers the latest exam objectives and provides a deep dive into essential IT auditing areas, including IT governance, systems development, and asset protection. The book follows a structured, three-step approach to solidify your understanding. First, it breaks down the fundamentals with clear, concise explanations. Then, it highlights critical exam-focused points to ensure you concentrate on key areas. Finally, it challenges you with self-assessment questions that reflect the exam format, helping you assess your knowledge.Additionally, you’ll gain access to online resources, including mock exams, interactive flashcards, and invaluable exam tips, ensuring you’re fully prepared for the exam with unlimited practice opportunities.By the end of this guide, you’ll be ready to pass the CISA exam with confidence and advance your career in auditing.
Aldo Marzullo, Enrico Deusebio, Claudio Stamile
Graph Machine Learning, Second Edition builds on its predecessor’s success, delivering the latest tools and techniques for this rapidly evolving field. From basic graph theory to advanced ML models, you’ll learn how to represent data as graphs to uncover hidden patterns and relationships, with practical implementation emphasized through refreshed code examples. This thoroughly updated edition replaces outdated examples with modern alternatives such as PyTorch and DGL, available on GitHub to support enhanced learning.The book also introduces new chapters on large language models and temporal graph learning, along with deeper insights into modern graph ML frameworks. Rather than serving as a step-by-step tutorial, it focuses on equipping you with fundamental problem-solving approaches that remain valuable even as specific technologies evolve. You will have a clear framework for assessing and selecting the right tools.By the end of this book, you’ll gain both a solid understanding of graph machine learning theory and the skills to apply it to real-world challenges.*Email sign-up and proof of purchase required -
Tarek A. Atwan
To use time series data to your advantage, you need to master data preparation, analysis, and forecasting. This fully refreshed second edition helps you unlock insights from time series data with new chapters on probabilistic models, signal processing techniques, and new content on transformers. You’ll work with the latest releases of popular libraries like Pandas, Polars, Sktime, stats models, stats forecast, Darts, and Prophet through up-to-date examples.You'll hit the ground running by ingesting time series data from various sources and formats and learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods.Through detailed instructions, you'll explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR, and learn practical techniques for handling non-stationary data using power transforms, ACF and PACF plots, and decomposing time series data with seasonal patterns. The recipes then level up to cover more advanced topics such as building ML and DL models using TensorFlow and PyTorch and applying probabilistic modeling techniques. In this part, you’ll also be able to evaluate, compare, and optimize models, finishing with a strong command of wrangling data with Python.