Suchergebnisse
Marc Boorshtein, Scott Surovich, Ed Price
Kubernetes – An Enterprise Guide, Third Edition, provides a practical and up-to-date resource for navigating modern cloud-native technologies. This edition covers advanced Kubernetes deployments, security best practices, and key strategies for managing enterprise workloads efficiently.The book explores critical topics such as virtual clusters, container security, and secrets management, offering actionable insights for running Kubernetes in production environments. Learn how to transition to microservices with Istio, implement GitOps and CI/CD for streamlined deployments, and enhance security using OPA/Gatekeeper and KubeArmor.Designed for professionals, this guide equips you with the knowledge to integrate Kubernetes with industry-leading tools and optimize business-critical applications. Stay ahead in the evolving cloud landscape with strategies that drive efficiency, security, and scalability.
William Ayd, Matthew Harrison, Wes McKinney
Unlock the full power of pandas 2.x with this hands-on cookbook, designed for Python developers, data analysts, and data scientists who need fast, efficient solutions for real-world data challenges. This book provides practical, ready-to-use recipes to streamline your workflow. With step-by-step guidance, you'll master data wrangling, visualization, performance optimization, and scalable data analysis using pandas’ most powerful features. From importing and merging large datasets to advanced time series analysis and SQL-like operations, this cookbook equips you with the tools to analyze, manipulate, and visualize data like a pro. Learn how to boost efficiency, optimize memory usage, and seamlessly integrate pandas with NumPy, PyArrow, and databases. This book will help you transform raw data into actionable insights with ease.*Email sign-up and proof of purchase required
Manu Joseph, Jeffrey Tackes, Christoph Bergmeir
Predicting the future, whether it's market trends, energy demand, or website traffic, has never been more crucial. This practical, hands-on guide empowers you to build and deploy powerful time series forecasting models. Whether you’re working with traditional statistical methods or cutting-edge deep learning architectures, this book provides structured learning and best practices for both.Starting with the basics, this data science book introduces fundamental time series concepts, such as ARIMA and exponential smoothing, before gradually progressing to advanced topics, such as machine learning for time series, deep neural networks, and transformers. As part of your fundamentals training, you’ll learn preprocessing, feature engineering, and model evaluation. As you progress, you’ll also explore global forecasting models, ensemble methods, and probabilistic forecasting techniques.This new edition goes deeper into transformer architectures and probabilistic forecasting, including new content on the latest time series models, conformal prediction, and hierarchical forecasting. Whether you seek advanced deep learning insights or specialized architecture implementations, this edition provides practical strategies and new content to elevate your forecasting skills.*Email sign-up and proof of purchase required