Proficiency in Bootstrap, AJAX, and jQuery is paramount in modern web development due to their significant contributions to creating engaging and functional web applications. Bootstrap, with its extensive library of pre-designed components and responsive grid system, expedites UI development while ensuring consistency and adaptability across various devices and screen sizes. AJAX empowers developers to implement dynamic and asynchronous communication between the client and server, enabling real-time updates without requiring full page reloads. This enhances user experience by providing smoother interactions and reducing latency, crucial for today's fast-paced digital environments. Further, jQuery simplifies client-side scripting by abstracting complex JavaScript operations into concise and reusable functions, facilitating efficient DOM manipulation, event handling, and AJAX requests. Mastery of these technologies not only aligns developers with industry standards but also enhances the employability opportunities by demonstrating their ability to create visually appealing, responsive, and interactive web applications that meet the evolving demands of users and businesses alike in the competitive web development landscape.
jQuery is a fast, lightweight, and feature-rich JavaScript library that simplifies HTML document traversal, event handling, and animation, enabling developers to create dynamic and interactive web applications with ease. Its concise syntax allows for rapid development, making it a popular choice for both beginners and experienced developers. In the industry, jQuery is important as it enhances cross-browser compatibility, reduces coding complexity, and accelerates the development process, allowing teams to focus on building engaging user experiences. Despite the rise of modern frameworks like React and Angular, jQuery remains relevant for maintaining legacy projects and is widely used in many existing websites and applications. The book covers essential jQuery concepts that are crucial for enhancing user skills in modern web application development.
This tells the story of Douglas Engelbart's revolutionary vision, reaching beyond conventional histories of Silicon Valley to probe the ideology that shaped some of the basic ingredients of contemporary life.
The very idea that the teachings can be mastered will arouse controversy within Buddhist circles. Even so, Ingram insists that enlightenment is an attainable goal, once our fanciful notions of it are stripped away, and we have learned to use meditation as a method for examining reality rather than an opportunity to wallow in self-absorbed mind-noise. Ingram sets out concisely the difference between concentration-based and insight (vipassana) meditation; he provides example practices; and most importantly he presents detailed maps of the states of mind we are likely to encounter, and the stages we must negotiate as we move through clearly-defined cycles of insight. Its easy to feel overawed, at first, by Ingram's assurance and ease in the higher levels of consciousness, but consistently he writes as a down-to-earth and compassionate guide, and to the practitioner willing to commit themselves this is a glittering gift of a book.In this new edition of the bestselling book, the author rearranges, revises and expands upon the original material, as well as adding new sections that bring further clarity to his ideas.
Statistics: Unlocking the Power of Data, 3rd Edition is designed for an introductory statistics course focusing on data analysis with real-world applications. Students use simulation methods to effectively collect, analyze, and interpret data to draw conclusions. Randomization and bootstrap interval methods introduce the fundamentals of statistical inference, bringing concepts to life through authentically relevant examples. More traditional methods like t-tests, chi-square tests, etc. are introduced after students have developed a strong intuitive understanding of inference through randomization methods. While any popular statistical software package may be used, the authors have created StatKey to perform simulations using data sets and examples from the text. A variety of videos, activities, and a modular chapter on probability are adaptable to many classroom formats and approaches.
Power Query is the amazing new data cleansing tool in both Excel and Power BI Desktop. Do you find yourself performing the same data cleansing steps day after day? Power Query will make it faster to clean your data the first time. While Power Query is powerful, the interface is subtle—there are tools hiding in plain sight that are easy to miss. Go beyond the obvious and take Power Query to new levels with this book.
Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
