College Physics


Book Description

College Physics conveys the fundamental concepts of algebra-based physics in a readable and concise manner. The authors emphasize the importance of conceptual understanding before solving problems numerically, use everyday life examples to keep students interested, and promote logical thinking to solve multiple step problems. The Seventh Edition of this text presents an especially clear learning path, places a strong emphasis on understanding concepts and problem-solving, and for the first time, includes a book-specific version of MasteringPhysics™.




College Physics Essentials, Eighth Edition


Book Description

This new edition of College Physics Essentials provides a streamlined update of a major textbook for algebra-based physics. This is the second volume covers electricity, atomic, nuclear, and quantum physics. The first volume is available separately and covers topics such as mechanics, heat, and thermodynamics. The authors provide emphasis on worked examples together with expanded problem sets that build from conceptual understanding to numerical solutions and real-world applications to increase reader engagement. Including over 900 images throughout the two volumes, this textbook is highly recommended for students seeking a basic understanding of key physics concepts and how to apply them to real problems.




College Physics


Book Description




College Physics (With Physicsnow)


Book Description

This is the Loose-leaf version offered through the Alternative Select - Freedom Titles program. Please contact your Custom Editor to order and for additional details.




Feyerabend’s Epistemological Anarchism


Book Description

This book argues that the traditional image of Feyerabend is erroneous and that, contrary to common belief, he was a great admirer of science. It shows how Feyerabend presented a vision of science that represented how science really works. Besides giving a theoretical framework based on Feyerabend ́s philosophy of science, the book offers criteria that can help readers to evaluate and understand research reported in important international science education journals, with respect to Feyerabend’s epistemological anarchism. The book includes an evaluation of general chemistry and physics textbooks. Most science curricula and textbooks provide the following advice to students: Do not allow theories in contradiction with observations, and all scientific theories must be formulated inductively based on experimental facts. Feyerabend questioned this widely prevalent premise of science education in most parts of the world, and in contrast gave the following advice: Scientists can accept a hypothesis despite experimental evidence to the contrary and scientific theories are not always consistent with all the experimental data. No wonder Feyerabend became a controversial philosopher and was considered to be against rationalism and anti-science. Recent research in philosophy of science, however, has shown that most of Feyerabend ́s philosophical ideas are in agreement with recent trends in the 21st century. Of the 120 articles from science education journals, evaluated in this book only 9% recognized that Feyerabend was presenting a plurality of perspectives based on how science really works. Furthermore, it has been shown that Feyerabend could even be considered as a perspectival realist. Among other aspects, Feyerabend emphasized that in order to look for breakthroughs in science one does not have to be complacent about the truth of the theories but rather has to look for opportunities to “break rules” or “violate categories.” Mansoor Niaz carefully analyses references to Feyerabend in the literature and displays the importance of Feyerabend’s philosophy in analyzing, historical episodes. Niaz shows through this remarkable book a deep understanding to the essence of science. - Calvin Kalman, Concordia University, Canada In this book Mansoor Niaz explores the antecedents, context and features of Feyerabend’s work and offers a more-nuanced understanding, then reviews and considers its reception in the science education and philosophy of science literature. This is a valuable contribution to scholarship about Feyerabend, with the potential to inform further research as well as science education practice.- David Geelan, Griffith University, Australia




Deep Learning


Book Description

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.







Physics


Book Description

Approaches the subject of physics from a contemporary viewpoint, integrating the Newtonian, relativistic and quantum description of nature. The text covers all the traditional topics of physics with greater emphasis on the conservation laws, the concepts of field and waves and the atomic view of matter.




Hbcu Today


Book Description