Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians.

Software development is hard, but creating good software is even harder, especially if your main job is something other than developing software. Engineer Your Software! opens the world of software engineering, weaving engineering techniques and measurement into software development activities. Focusing on architecture and design, Engineer Your Software! claims that no matter how you write software, design and engineering matter and can be applied at any point in the process. Engineer Your Software! provides advice, patterns, design criteria, measures, and techniques that will help you get it right the first time. Engineer Your Software! also provides solutions to many vexing issues that developers run into time and time again. Developed over 40 years of creating large software applications, these lessons are sprinkled with real-world examples from actual software projects. Along the way, the author describes common design principles and design patterns that can make life a lot easier for anyone tasked with writing anything from a simple script to the largest enterprise-scale systems.

This career guide explains the software developer role in the context of the industry, including the relevant skills and competencies you will need to become a software developer. Discussion of popular programming languages is covered, as well as tools and techniques of the trade. Career progression tips and software developer case studies round off the book, providing you with the insider knowledge you need to kick start your software development journey.

Even amazing products can be let down by poor user interfaces. It is the job of front-end developers to make software products and websites engaging and attractive for users. This book covers the role of front-end developer in terms of typical responsibilities, required skills and relevant tools, methods and techniques. Career progression for front-end developers is also discussed.

Artificial intelligence (AI) has become pervasive in most areas of research and applications. While computation can significantly reduce mental efforts for complex problem solving, effective computer algorithms allow continuous improvement of AI tools to handle complexity―in both time and memory requirements―for machine learning in large datasets. Meanwhile, data science is an evolving scientific discipline that strives to overcome the hindrance of traditional skills that are too limited to enable scientific discovery when leveraging research outcomes. Solutions to many problems in medicine and life science, which cannot be answered by these conventional approaches, are urgently needed for society.

Machine learning (ML) and deep learning (DL) algorithms are invaluable resources for Industry 4.0 and allied areas and are considered as the future of computing. A subfield called neural networks, to recognize and understand patterns in data, helps a machine carry out tasks in a manner similar to humans. The intelligent models developed using ML and DL are effectively designed and are fully investigated – bringing in practical applications in many fields such as health care, agriculture and security. These algorithms can only be successfully applied in the context of data computing and analysis. Today, ML and DL have created conditions for potential developments in detection and prediction.

Learn to be a Python expert in easy lessons! Key Features Acquire knowledge of Python programming simply and easily. Learn about object-oriented programming and how it applies to Python. Make a splash with list comprehensions, generators, and decorators...

Be a pro with a step-by-step guide to learning Python programming and get real results.

Python is a high-level, open-source programming language designed for use with a wide variety of operating systems. Due to its dynamic and diversified nature, it is regarded as the most robust programming language. With simple syntax, Python is easy-to-use and people who learn it for the first time find it very easy to catch the concepts. Having used pioneering websites such as YouTube, DropBox, Python is in high market demand. Get a copy of this book if you'd like to take full advantage of Python.

Data Structure is a way of collecting and organising data in such a way that we can perform operations on these data in an effective way. Data structure is about rendering data elements in terms of some relationship, for better organisation and storage. For example, we have some data which has, distance and location in the example. The "location" is of String data type and distance is of integer data type.

Kids deserve a better digital future. Help them create it.

When it comes to raising children in a digital world, every parent feels underprepared and overwhelmed. We worry that our children will become addicted to online games, be victims of cyberbullying, or get lost down the rabbit hole of social media. We warn them about all the things they shouldn't do online, but we don't do nearly enough to teach them the skills of digital well-being.