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An encyclopedia designed especially to meet the needs of elementary, junior high, and senior high school students.
Helps aspiring college students discover where their strengths truly lie and how to develop them to reach their full potential at school and later in the real world.
Come and explore the world under your feet with the Dirtmeister and friends! Part graphic novel, part fun guidebook, this very cool, rocky journey introduces both eager and reluctant readers to the basic geologic processes that shape our Earth. Clear and concise explanations of the various geologic processes reveal the comprehensive science behind each fascinating topic. Fun facts and simple DIY experiments reinforce the concepts while short biographies of important scientists inspire future geo-scientists.
A lively read from a working teacher offers practical engagement strategies for students with attention challenges If learning is a motor, student engagement is the key. But when teaching students with ADHD and other attention challenges, sometimes even the most finely tuned classroom can sputter. Teach for Attention! is your tool belt of teaching strategies for students with ADHD, low self-confidence, distraction, and other attention challenges. Dozens of true classroom stories show the strategies in action. It’s all about making simple fixes so you can reach every student without changing your approach or revamping your curriculum. Carry these ideas with you like tools on a belt—the right one will be there when you need it!
Cryptography is now ubiquitous – moving beyond the traditional environments, such as government communications and banking systems, we see cryptographic techniques realized in Web browsers, e-mail programs, cell phones, manufacturing systems, embedded software, smart buildings, cars, and even medical implants. Today's designers need a comprehensive understanding of applied cryptography. After an introduction to cryptography and data security, the authors explain the main techniques in modern cryptography, with chapters addressing stream ciphers, the Data Encryption Standard (DES) and 3DES, the Advanced Encryption Standard (AES), block ciphers, the RSA cryptosystem, public-key cryptosystems based on the discrete logarithm problem, elliptic-curve cryptography (ECC), digital signatures, hash functions, Message Authentication Codes (MACs), and methods for key establishment, including certificates and public-key infrastructure (PKI). Throughout the book, the authors focus on communicating the essentials and keeping the mathematics to a minimum, and they move quickly from explaining the foundations to describing practical implementations, including recent topics such as lightweight ciphers for RFIDs and mobile devices, and current key-length recommendations. The authors have considerable experience teaching applied cryptography to engineering and computer science students and to professionals, and they make extensive use of examples, problems, and chapter reviews, while the book’s website offers slides, projects and links to further resources. This is a suitable textbook for graduate and advanced undergraduate courses and also for self-study by engineers.
Textbooks are symbols of centuries-old education. They're often outdated as soon as they hit students' desks. Acting "by the textbook" implies compliance and a lack of creativity. It's time to ditch those textbooks--and those textbook assumptions about learning In Ditch That Textbook, teacher and blogger Matt Miller encourages educators to throw out meaningless, pedestrian teaching and learning practices. He empowers them to evolve and improve on old, standard, teaching methods. Ditch That Textbook is a support system, toolbox, and manifesto to help educators free their teaching and revolutionize their classrooms.
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.
The author of the best-selling What the Best College Teachers Do is back with more humane, doable, and inspiring help, this time for students who want to get the most out of college—and every other educational enterprise, too. The first thing they should do? Think beyond the transcript. The creative, successful people profiled in this book—college graduates who went on to change the world we live in—aimed higher than straight A’s. They used their four years to cultivate habits of thought that would enable them to grow and adapt throughout their lives. Combining academic research on learning and motivation with insights drawn from interviews with people who have won Nobel Prizes, Emmys, fame, or the admiration of people in their field, Ken Bain identifies the key attitudes that distinguished the best college students from their peers. These individuals started out with the belief that intelligence and ability are expandable, not fixed. This led them to make connections across disciplines, to develop a “meta-cognitive” understanding of their own ways of thinking, and to find ways to negotiate ill-structured problems rather than simply looking for right answers. Intrinsically motivated by their own sense of purpose, they were not demoralized by failure nor overly impressed with conventional notions of success. These movers and shakers didn’t achieve success by making success their goal. For them, it was a byproduct of following their intellectual curiosity, solving useful problems, and taking risks in order to learn and grow.