An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Helping you get to grips with online learning, this book contains a wealth of practical tips and strategies that will make studying online easier. Covering the advantages of online learning as well as the problems you might face, this book provides tried and tested advice to help you overcome those difficulties so that you can work to the best of your abilities. Identifying techniques designed specifically for studying online, this key guide explores topics and methods such as: the differences between traditional and online study, preparing for online study as well as planning and organising; making sole working a collaborative and shared experience; reading online, online notetaking, using study forums, using video, collaboration, and coping with online exams; understanding the possible effects on mental and physical health and how to cope with the distractions the virtual world can bring while taking care of your mental and physical health. With step-by-step instructions for each of the techniques, as well as guidance on using online study software to the best effect, this must-have student companion provides tips and tricks to make university distance studying both effective and enjoyable. Visit the accompanying website here: https://studyingonline.tips

A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

How employable will you be when you graduate from your business and management degree? How can you ensure that your time as a student is spent developing skills essential to the business world? Will you be poised to take on the job market with confidence and land your dream job? This study guide bridges the gap between your degree and your future career by connecting your study skills to the professional ones you’ll need. Designed to be a companion throughout your degree, this easy-to-use reference work simultaneously develops your employability whilst also helping you to succeed at university. Throughout your studies it will keep you focused on your future career by: teaching ‘bridging skills’ that enable you to apply your learning to professional practice showing how study skills such as diagnostics, planning and management, critical reading and knowledge transformation are used in the workplace demonstrating why ‘thinking skills’ such as critical thinking and reflection, developing arguments, problem solving, decision making, creative thinking and ethical thinking are vital to employers helping you to understand, early in your degree, what employers are looking for so that you can develop ‘career readiness’ as you study and gain work experience guiding you in developing a unique, evidence-based CV and using self-knowledge to make the right career choice. Studying for your Future Employability provides a range of scenarios and activities to demonstrate the links between study skills and professional skills, along with techniques familiar in the workplace. With IT skills embedded throughout, this is the perfect study skills textbook to accompany business and management students who want to make their time in education count.

Internet Studies has been one of the most dynamic and rapidly expanding interdisciplinary fields to emerge over the last decade. The Oxford Handbook of Internet Studies has been designed to provide a valuable resource for academics and students in this area, bringing together leading scholarly perspectives on how the Internet has been studied and how the research agenda should be pursued in the future. The Handbook aims to focus on Internet Studies as an emerging field, each chapter seeking to provide a synthesis and critical assessment of the research in a particular area. Topics covered include social perspectives on the technology of the Internet, its role in everyday life and work, implications for communication, power, and influence, and the governance and regulation of the Internet. The Handbook is a landmark in this new interdisciplinary field, not only helping to strengthen research on the key questions, but also shape research, policy, and practice across many disciplines that are finding the Internet and its political, economic, cultural, and other societal implications increasingly central to their own key areas of inquiry.

This book examines important advances and offers a realistic image of the state of the art in student learning outcomes assessment in higher education—a field close to the core of nearly every higher education institution. Producing sound information on what students know and can do is critical to higher education practitioners and future social prosperity. Spanning international, national and institutional developments, the book presents methodological and empirical insights, highlights research challenges, and showcases the enormous progress made in recent years. The book will be of interest to researchers in education assessment and neighbouring fields, and stakeholders like institutional leaders, teachers and graduate employers looking for better insight on returns, governments searching for information to assist with funding and regulation, and members of the public wanting more clarity about outcomes and public investment. This book was originally published as a special issue of Assessment & Evaluation in Higher Education.