Introduction to JavaScript Object Notation

Explaining how to create professional looking films, this detailed handbook takes readers step by step through the filmmaking process, from filming a movie, through the editing process, to distributin

This book will serve as a framework for you as a software engineer seeking a fulfilling career and wishing to stay passionate and maintain a healthy mental state. It is filled with protocols to achieve effective life-long learning, navigate career development, adapt to changes, maintain work-life balance, and have a healthy lifestyle.As a successful software engineer you tend to focus on improving your technical skills: learning a new programming language, mastering another tool, or using a library. But you also need to build a solid mental framework that will help you navigate your professional development. You need to develop the skills that will help you be a happy software engineer.This book will help you if you feel frustrated, unmotivated, or unhappy; lost in your career path; or uncertain if you want to be a software engineer. It can help you deal with burnout, high levels of stress, or depression; or if you struggle to be productive while working from home. What You Will LearnE

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

Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations. The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated. After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python. What You Will LearnUse Python and numerical computation to demonstrate the power of simulationChoose a paradigm to run a simulationDraw statistical insights from numerical experimentsKnow how simulation is used to solve real-world problems Who This Book Is ForEntry-level to mid-level Python developers from various backg