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Information and Coding Theory
As this Preface is being written, the twentieth century is coming to an end.Historians may perhaps come to refer to it as the century of information, just as its predecessor is associated with the process of industrialisation.Successive technological developments such as the telephone, radio, television, computers and the Internet have had profound effects on the way we live.We can see pic tures of the surface of Mars or the early shape of the Universe.The contents of a whole shelf-load of library books can be compressed onto an almost weight less piece of plastic.Billions of people can watch the same football match, or can keep in instant touch with friends around the world without leaving home.In short, massive amounts of information can now be stored, transmitted and processed, with surprising speed, accuracy and economy.Of course, these developments do not happen without some theoretical ba sis, and as is so often the case, much of this is provided by mathematics.Many of the first mathematical advances in this area were made in the mid-twentieth century by engineers, often relying on intuition and experience rather than a deep theoretical knowledge to lead them to their discoveries.Soon the math ematicians, delighted to see new applications for their subject, joined in and developed the engineers' practical examples into wide-ranging theories, com plete with definitions, theorems and proofs.
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Programming Machine Learning : From Coding to Deep Learning
You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool.But where to start? It's easy to be intimidated, even as a software developer.The good news is that it doesn't have to be that hard.Master machine learning by writing code one line at a time, from simple learning programs all the way to a true deep learning system.Tackle the hard topics by breaking them down so they're easier to understand, and build your confidence by getting your hands dirty.Peel away the obscurities of machine learning, starting from scratch and going all the way to deep learning.Machine learning can be intimidating, with its reliance on math and algorithms that most programmers don't encounter in their regular work.Take a hands-on approach, writing the Python code yourself, without any libraries to obscure what's really going on.Iterate on your design, and add layers of complexity as you go.Build an image recognition application from scratch with supervised learning.Predict the future with linear regression. Dive into gradient descent, a fundamental algorithm that drives most of machine learning.Create perceptrons to classify data. Build neural networks to tackle more complex and sophisticated data sets.Train and refine those networks with backpropagation and batching.Layer the neural networks, eliminate overfitting, and add convolution to transform your neural network into a true deep learning system.Start from the beginning and code your way to machine learning mastery.What You Need: The examples in this book are written in Python, but don't worry if you don't know this language: you'll pick up all the Python you need very quickly.Apart from that, you'll only need your computer, and your code-adept brain.
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Information Theory, Inference and Learning Algorithms
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography.The book introduces theory in tandem with applications.Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction.Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks.Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast.Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses.It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
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The Political Lives of Information : Information and the Production of Development in India
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Is learning programming and software development very challenging?
Learning programming and software development can be challenging for some people, as it requires logical thinking, problem-solving skills, and attention to detail. However, with dedication, practice, and the right resources, it is definitely achievable. Breaking down complex concepts into smaller, more manageable parts and seeking help from online tutorials, courses, and communities can make the learning process easier and more enjoyable. Ultimately, the level of challenge will vary depending on the individual's background, experience, and learning style.
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How can I obtain information on learning C programming?
You can obtain information on learning C programming by accessing online resources such as tutorials, forums, and websites dedicated to programming. There are also many books available on the topic that can provide comprehensive information and guidance on learning C programming. Additionally, you can consider enrolling in a programming course or workshop either in-person or online to receive structured instruction and support in learning C programming.
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Which programming languages are used in software development?
There are many programming languages used in software development, including popular languages such as Java, Python, C++, JavaScript, and Ruby. Each language has its own strengths and is used for different purposes in software development. For example, Java is commonly used for building enterprise-level applications, while Python is known for its simplicity and versatility. C++ is often used for system software and game development, while JavaScript is essential for web development. Overall, the choice of programming language depends on the specific requirements of the software being developed.
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What is the difference between software development and programming?
Software development is a broader term that encompasses the entire process of creating software, including planning, designing, testing, and maintaining software applications. Programming, on the other hand, refers specifically to the act of writing code to instruct a computer to perform certain tasks. While programming is a key component of software development, software development involves a more comprehensive approach that includes various stages beyond just writing code.
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Spatial Information Technology for Sustainable Development Goals
This textbook aims to develop a scientific knowledge base on spatial information technology to communicate the United Nations' Sustainable Development Goals (SDGs) among students, researchers, professionals and laymen.The book improves understanding of the spatial database and explains how to extract information from this for planning purposes.To enhance the knowledge of geoscientists and environmentalists, the book describes the basic fundamental concepts to advance techniques for spatial data management and analysis and discusses the methodology.The Geographic Information System (GIS), remote sensing and Global Positioning System (GPS) are presented in an integrated manner for the planning of resources and infrastructure.The management of these systems is discussed in a very lucid way to develop the reader's skills.The proper procedure for map making and spatial analysis are included along with case studies to the reader.Where thefirst part of the book discusses the conceptual background, the second part deals with case studies using these applications in different disciplines.The presented case studies include land use, agriculture, flood, watershed characterization and infrastructure assessment for the Sustainable Development Goals.
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Critical ICT4D (Information and Communication Technologies for Development)
The edited volume Critical ICT4D highlights the need for a paradigm change in theorising, designing, and researching Information and Communication Technologies for Development (ICT4D).Engaging authors from the Majority World and entering a process of restoring epistemic justice in knowledge production and ownership, the text:Reflects on the histories and narratives around development programmes, their deep-rooted socio-political background, and the power relations integrated into or induced by such measuresProblematises the current scholarship and practices through decolonial and pluralistic approaches built with an explicit perspective of resisting epistemic violenceConstructs justice-enacting engagements of technologies with society. Offering thematic discussions in many development sectors with up-to-date case studies informed by recent research in the field, it sheds light on constructive contributions of critical ICT4D research.Written in accessible language, the book will appeal to postgraduate students, fellow researchers, policymakers in the fields of sociology, development studies, STS, critical data studies, surveillance studies, international relations, public administration, and information systems. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution (CC-BY) 4.0 license.
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Transforming Qualitative Information : Thematic Analysis and Code Development
Thematic analysis, a process for encoding qualitative information can be thought of as a bridge between the language of qualitative research and the language of quantitative research.Author Richard E. Boyatzis helps researchers understand thematic analysis a process that is a part of many qualitative methods and provides clear guidelines about learning to develop techniques to apply it to one's own research.Transforming Qualitative Information shows how to sense themes, the first step in analyzing information as well as how to develop codes, through the use of numerous examples from myriad research settings.Research design issues that are essential to rigorous and high-quality use of qualitative information are addressed, such as identifying, sampling, scoring and scaling, and reliability.This original volume confronts the debate between positivist and postmodernist looking at the research act in an innovative and fresh way.Boyatzis argues for an ecumenical approach to doing research.His book will be invaluable to researchers across a broad spectrum of disciplines and approaches.
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Information for Sustainable Development : Technology, People and Society
Information for Sustainable Development is a landmark publication that examines the perspectives, challenges and progress towards achieving the targets of the UN sustainable development goals (SDGs), through the lens of information science.Written by an author team with extensive experience in the research and practice of information and sustainability, the book provides a thorough introduction to the SDGs and the impact of information, data, people and society on measuring performance and assessing progress in achieving the SDG goals. Split into four distinct sections, the book provides an introduction to the landscape for information, data and metadata in the context of the SDGs, before exploring key topics such as:how metadata is used in measuring progress and success, and the challenges and complexities of calculation methods and the interpretation of datadigital literacy and the digital divide across different countries and regions, and how critical information skills are in achieving success in the SDGsspecific human and social challenges associated with the SDGseducation for sustainable development and the role of environmental literacyan examination of the research and development in the information sector around green libraries, climate change and sustainability, including a proposed research and training framework for future information science research. This book will be a valuable resource for researchers, students and professionals in information and computer sciences as well as disciplines such as politics, business and education.It will provide inspiration and new discussion on how the information, data, people and societal elements of the SDGs should be considered and embedded in future research and training activity.
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What is the difference between an application developer and an information technology assistant in software development?
An application developer is responsible for designing, coding, and testing software applications, while an information technology assistant in software development typically provides support to the development team by troubleshooting technical issues, maintaining software systems, and assisting with software implementation. The application developer focuses on creating new software solutions, while the IT assistant supports the development process by ensuring the smooth functioning of existing software systems. Additionally, the application developer typically has a deeper understanding of programming languages and software development methodologies, while the IT assistant may have a broader knowledge of IT systems and infrastructure.
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What training opportunities are available for IT specialists to specialize in web development and general programming, such as software development?
There are various training opportunities available for IT specialists looking to specialize in web development and general programming. Online platforms like Coursera, Udemy, and Codecademy offer courses and certifications in programming languages such as Python, Java, and JavaScript. Additionally, coding bootcamps like General Assembly and Flatiron School provide intensive, hands-on training in software development. IT specialists can also pursue advanced degrees in computer science or related fields to deepen their knowledge and skills in web development and programming.
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What training options are available for IT specialists to specialize in web development and general programming, such as software development?
IT specialists looking to specialize in web development and general programming have a variety of training options available to them. They can pursue formal education through degree programs in computer science or related fields, attend coding bootcamps that offer intensive training in programming languages and frameworks, or take online courses and tutorials to learn specific skills. Additionally, IT specialists can participate in workshops, seminars, and conferences to stay updated on the latest trends and technologies in web development and software development. Continuous learning and practice are essential for IT specialists to excel in these specialized areas.
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Which programming language is suitable for software development for the PC?
There are several programming languages that are suitable for software development for the PC, but some of the most popular and widely used ones include C++, Java, and C#. C++ is a powerful and versatile language that is commonly used for developing system software and applications that require high performance. Java is a popular choice for developing cross-platform applications, as it can run on any operating system that has a Java Virtual Machine. C# is commonly used for developing Windows applications and is well-integrated with the .NET framework. Ultimately, the choice of programming language depends on the specific requirements of the software being developed and the preferences of the development team.
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