The Pandas Workshop. A comprehensive guide to using Python for data analysis with real-world case studies

Blaine Bateman, Saikat Basak, Thomas V. Joseph, William So

The Pandas Workshop will teach you how to be more productive with data and generate real business insights to inform your decision-making. You will be guided through real-world data science problems and shown how to apply key techniques in the context of realistic examples and exercises. Engaging activities will then challenge you to apply your new skills in a way that prepares you for real data science projects.You’ll see how experienced data scientists tackle a wide range of problems using data analysis with pandas. Unlike other Python books, which focus on theory and spend too long on dry, technical explanations, this workshop is designed to quickly get you to write clean code and build your understanding through hands-on practice. As you work through this Python pandas book, you’ll tackle various real-world scenarios, such as using an air quality dataset to understand the pattern of nitrogen dioxide emissions in a city, as well as analyzing transportation data to improve bus transportation services.By the end of this data analytics book, you’ll have the knowledge, skills, and confidence you need to solve your own challenging data science problems with pandas.

ServiceStack 4 Cookbook. Over 70 recipes to create web services, build message-based apps, and work with object-relational mapping

Kyle Hodgson, Darren Reid

Oracle Essbase 11 Development Cookbook. Over 90 advanced development recipes to build and take your Oracle Essbase Applications further with this book and

Jose R Ruiz, Jose R. Ruiz

Oracle Essbase is a Multi-Dimensional Online Analytical Processing (OLAP) server, providing a rich environment for effectively developing custom analytic and enterprise performance management applications. Oracle Essbase enables business users to quickly model complex business scenarios.This practical cookbook shows you the advanced development techniques when building Essbase Applications and how to take these applications further.Packed with over 90 task-based and immediately reusable recipes, this book starts by showing you how to use a relational data model to build and load an Essbase cube and how to create a data source, prepare the mini schema, and work with the data elements in Essbase Studio. The book then dives into topics such as building the BSO cube, building the ASO cube, using EAS for development, creating Calculation Scripts and using MaxL to automate processes.

Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications

Valery Manokhin, Agus Sudjianto

In the rapidly evolving landscape of machine learning, the ability to accurately quantify uncertainty is pivotal. Practical Guide to Applied Conformal Prediction in Python addresses this need by offering an in-depth exploration of Conformal Prediction, a cutting-edge framework set to revolutionize uncertainty management in various ML applications.Embark on a comprehensive journey through Conformal Prediction, exploring its fundamentals and practical applications in binary classification, regression, time series forecasting, imbalanced data, computer vision, and NLP. Each chapter delves into specific aspects, offering hands-on insights and best practices for enhancing prediction reliability. The book concludes with a focus on multi-class classification nuances, providing expert-level proficiency to seamlessly integrate Conformal Prediction into diverse industries. Practical examples in Python using real-world datasets reinforce intuitive explanations, ensuring you acquire a robust understanding of this modern framework for uncertainty quantification.This guide is a beacon for mastering Conformal Prediction in Python, providing a blend of theory and practical application. It serves as a comprehensive toolkit to enhance machine learning skills, catering to professionals from data scientists to ML engineers.

Learn Quantum Computing with Python and IBM Quantum. Write your own practical quantum programs with Python - Second Edition

Robert Loredo

The IBM Quantum Platform was built to enable developers to learn the basics of quantum computing by providing access to high performant quantum computers and provide documentation and courses to help get up to speed with the latest features in quantum computing. Updated with new examples and changes to the platform, this edition begins with an introduction to the IBM Quantum Platform and the Quantum Information Science Kit (Qiskit) SDK. You will become well versed in the IBM Quantum Composer interface as well as running your quantum circuits on a real quantum computer. Along the way, you’ll learn some of the fundamental principles regarding quantum mechanics, qubits, quantum gates, quantum circuits, and the error mitigation techniques that are used to perform operations on qubits. As you build on your knowledge, you’ll understand the functionality of IBM Qiskit and the developer-focused resources so you can create your own quantum algorithms. You’ll learn how to monitor and optimize your quantum circuits. Lastly, you’ll look at the fundamental quantum algorithms and understand how they can be applied effectively. By the end of this quantum computing book, you'll know how to build quantum algorithms and will have gained a practical understanding of quantum computation that you can apply to your research or business.

Infrastructure Monitoring with Amazon CloudWatch. Effectively optimize resource allocation, detect anomalies, and set automated actions on AWS

Ewere Diagboya

CloudWatch is Amazon’s monitoring and observability service, designed to help those in the IT industry who are interested in optimizing resource utilization, visualizing operational health, and eventually increasing infrastructure performance. This book helps IT administrators, DevOps engineers, network engineers, and solutions architects to make optimum use of this cloud service for effective infrastructure productivity.You’ll start with a brief introduction to monitoring and Amazon CloudWatch and its core functionalities. Next, you’ll get to grips with CloudWatch features and their usability. Once the book has helped you develop your foundational knowledge of CloudWatch, you’ll be able to build your practical skills in monitoring and alerting various Amazon Web Services, such as EC2, EBS, RDS, ECS, EKS, DynamoDB, AWS Lambda, and ELB, with the help of real-world use cases. As you progress, you'll also learn how to use CloudWatch to detect anomalous behavior, set alarms, visualize logs and metrics, define automated actions, and rapidly troubleshoot issues. Finally, the book will take you through monitoring AWS billing and costs.By the end of this book, you'll be capable of making decisions that enhance your infrastructure performance and maintain it at its peak.

Regression Analysis with Python. Discover everything you need to know about the art of regression analysis with Python, and change how you view data

Luca Massaron, Alberto Boschetti

Regression is the process of learning relationships between inputs and continuous outputs from example data, which enables predictions for novel inputs. There are many kinds of regression algorithms, and the aim of this book is to explain which is the right one to use for each set of problems and how to prepare real-world data for it. With this book you will learn to define a simple regression problem and evaluate its performance. The book will help you understand how to properly parse a dataset, clean it, and create an output matrix optimally built for regression. You will begin with a simple regression algorithm to solve some data science problems and then progress to more complex algorithms. The book will enable you to use regression models to predict outcomes and take critical business decisions. Through the book, you will gain knowledge to use Python for building fast better linear models and to apply the results in Python or in any computer language you prefer.

Microsoft Dynamics AX 2009 Development Cookbook. Solve real-world Microsoft Dynamics AX development problems with over 60 simple but incredibly effective recipes with this book and

Mindaugas Pocius

Microsoft Dynamics AX provides a comprehensive Enterprise Resource Planning (ERP) solution for mid-size and larger organizations. Dynamics AX implementations are used worldwide by thousands of customers. With the new version - Dynamics AX 2009 - the system is due to expand even more rapidly.Every new implementation requires some level of customization, and all organizations want this to be done to the highest standards using proven approaches. This step-by-step guide will help you manage your company's ERP information and operations efficiently, and solve your business process problems in an effective and quick way. This book focuses on commonly used custom modifications in major Dynamics AX modules. This book contains commonly used bits of code which were real-world tested in at least one successful Dynamics AX implementation. Many of the recipes were deployed in many implementations and even across several versions of Dynamics AX. The examples in this book cover various areas of Dynamics AX to help developers not only learn about programming, but also about the functional side of Dynamics AX. The book should help developers who already know the basics of Dynamics AX programming to step up to the next level.The recipes allow you to look at the development from the perspective of business processes. You will learn to enhance your user interface using various Dynamics AX UI elements. Managing your data and functions will become easier. You will also get numerous development tips and tricks from a Dynamics AX development expert.