Introduction to Python Programming And Data Structure By Liang

Augment your knowledge of Python with this entertaining learning guide, which features 100 exercises and programming puzzles and solutions. Python Challenges will help prepare you for your next exam or a job interview, and covers numerous practical topics such as strings, data structures, recursion, arrays, and more.Each topic is addressed in its own separate chapter, starting with an introduction to the basics and followed by 10 to 15 exercises of various degrees of difficulty, helping you to improve your programming skills effectively. Detailed sample solutions, including the algorithms used for all tasks, are included to maximize your understanding of each area. Author Michael Inden also describes alternative solutions and analyzes possible pitfalls and typical errors.Three appendices round out the book: the first covers the Python command line interpreter, which is often helpful for trying out the code snippets and examples in the book, followed by an overview of Pytest for unit te

Migrate from pandas and scikit-Learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools. Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and machine learning with PySpark. You will learn to translate Python code from pandas/scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular machine learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Na鴳e Bayes, and neural networks. After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary to apply these methods using

Follow this comprehensive guide as it provides you with a deep understanding of Azure security principles, best practices, and implementation strategies aligned with the NIST Cybersecurity Framework (CSF). The book covers various topics from Azure security to designing and deploying solutions for infrastructure, data, and applications, including identify, protect, detect, respond, and recover solutions, in line with the NIST CSF.The book will take you through an introduction and the basic requirements for cloud security aligned with the NIST CSF. And then it will teach you how to design and deploy security for infrastructure, data, and apps security in an Azure enterprise environment. The book covers the NIST CSF and various cloud services offered by Microsoft Azure, maps each service against the NIST CSF, and explains each section with design and deployment considerations from a cybersecurity viewpoint.After reading this book, you will understand NIST CSF alignment with Microsoft Azur