| Author | : Victoria Bernhardt |
| Publisher | : Routledge |
| Total Pages | : 129 |
| Release | : 2013-11-20 |
| Genre | : Education |
| ISBN | : 1317930770 |
The latest book from best-selling author Victoria L. Bernhardt is an easy-to-read primer that describes what it takes to achieve student learning growth at every grade level, in every subject area, and with every student group.
| Author | : Victoria L. Bernhardt |
| Publisher | : Eye On Education |
| Total Pages | : 122 |
| Release | : 2009 |
| Genre | : Business & Economics |
| ISBN | : 1596671025 |
This book is an easy-to-read primer that describes what it takes to increase student achievement at every grade level, subject area, and student group. Readers will learn how to use data to drive their continuous improvement process as they develop an appreciation of the various types of data, uses for data, and how data are involved with the school improvement process. Online Course Available through a partnerhip with Knowledge Delivery Systems. Click here for more information. (CEUs may be available through your district.)
| Author | : Victoria L. Bernhardt |
| Publisher | : Routledge |
| Total Pages | : 97 |
| Release | : 2015-08-14 |
| Genre | : Education |
| ISBN | : 1317432053 |
The latest book from best-selling author Victoria L. Bernhardt is an easy-to-read primer that describes what it takes to achieve student learning growth at every grade level, in every subject area, and with every student group. In this new edition, readers will learn how to use data to inform their continuous school improvement as they develop an appreciation of the various types of data, uses for data, and how data are involved in the process. This accessible, updated edition provides a wealth of straightforward and accessible strategies that will allow educators to become comfortable with the many uses of data in increasing student improvement. Data, Data Everywhere, 2nd edition, provides a framework and summary of the continuous school improvement framework. It is a perfect resource for teachers, administrators, support staff, and students of leadership to guide comprehensive school improvement that will make a difference for all students.
| Author | : Richard Cooper |
| Publisher | : Springer |
| Total Pages | : 272 |
| Release | : 2007-08-19 |
| Genre | : Computers |
| ISBN | : 3540733906 |
This book features the refereed proceedings from the 24th British National Conference on Databases, held in Glasgow, Scotland in July 2007. The eighteen full papers and seven poster papers are presented, together with two invited contributions. Papers are organized into topical sections covering data applications, searching XML documents, querying XML documents, XML transformation, clustering and security, data mining, and extraction.
| Author | : Giorgia Lupi |
| Publisher | : Chronicle Books |
| Total Pages | : 304 |
| Release | : 2016-09-13 |
| Genre | : Design |
| ISBN | : 1616895462 |
Equal parts mail art, data visualization, and affectionate correspondence, Dear Data celebrates "the infinitesimal, incomplete, imperfect, yet exquisitely human details of life," in the words of Maria Popova (Brain Pickings), who introduces this charming and graphically powerful book. For one year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, mapped the particulars of their daily lives as a series of hand-drawn postcards they exchanged via mail weekly—small portraits as full of emotion as they are data, both mundane and magical. Dear Data reproduces in pinpoint detail the full year's set of cards, front and back, providing a remarkable portrait of two artists connected by their attention to the details of their lives—including complaints, distractions, phone addictions, physical contact, and desires. These details illuminate the lives of two remarkable young women and also inspire us to map our own lives, including specific suggestions on what data to draw and how. A captivating and unique book for designers, artists, correspondents, friends, and lovers everywhere.
| Author | : Jaime Lester |
| Publisher | : Routledge |
| Total Pages | : 290 |
| Release | : 2018-08-06 |
| Genre | : Education |
| ISBN | : 1351400525 |
Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and consent. Designed to give readers a practical and theoretical foundation in learning analytics and how data can support student success in higher education, this book is a valuable resource for scholars and administrators.
| Author | : Avrim Blum |
| Publisher | : Cambridge University Press |
| Total Pages | : 433 |
| Release | : 2020-01-23 |
| Genre | : Computers |
| ISBN | : 1108617360 |
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
| Author | : Keith McNulty |
| Publisher | : CRC Press |
| Total Pages | : 266 |
| Release | : 2022-06-19 |
| Genre | : Business & Economics |
| ISBN | : 100059727X |
Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation of graph methods in R and Python for the analysis of people and organizational networks. Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form. The book explores critical elements of network analysis in detail, including the measurement of distance and centrality, the detection of communities and cliques, and the analysis of assortativity and similarity. An extension chapter offers an introduction to graph database technologies. Real data sets from various research contexts are used for both instruction and for end of chapter practice exercises and a final chapter contains data sets and exercises ideal for larger personal or group projects of varying difficulty level. Key features: Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples.
| Author | : Rishal Hurbans |
| Publisher | : Simon and Schuster |
| Total Pages | : 392 |
| Release | : 2020-07-20 |
| Genre | : Computers |
| ISBN | : 1638355681 |
"From start to finish, the best book to help you learn AI algorithms and recall why and how you use them." - Linda Ristevski, York Region District School Board ”This book takes an impossibly broad area of computer science and communicates what working developers need to understand in a clear and thorough way.” - David Jacobs, Product Advance Local Key Features Master the core algorithms of deep learning and AI Build an intuitive understanding of AI problems and solutions Written in simple language, with lots of illustrations and hands-on examples Creative coding exercises, including building a maze puzzle game and exploring drone optimization About The Book “Artificial intelligence” requires teaching a computer how to approach different types of problems in a systematic way. The core of AI is the algorithms that the system uses to do things like identifying objects in an image, interpreting the meaning of text, or looking for patterns in data to spot fraud and other anomalies. Mastering the core algorithms for search, image recognition, and other common tasks is essential to building good AI applications Grokking Artificial Intelligence Algorithms uses illustrations, exercises, and jargon-free explanations to teach fundamental AI concepts.You’ll explore coding challenges like detecting bank fraud, creating artistic masterpieces, and setting a self-driving car in motion. All you need is the algebra you remember from high school math class and beginning programming skills. What You Will Learn Use cases for different AI algorithms Intelligent search for decision making Biologically inspired algorithms Machine learning and neural networks Reinforcement learning to build a better robot This Book Is Written For For software developers with high school–level math skills. About the Author Rishal Hurbans is a technologist, startup and AI group founder, and international speaker. Table of Contents 1 Intuition of artificial intelligence 2 Search fundamentals 3 Intelligent search 4 Evolutionary algorithms 5 Advanced evolutionary approaches 6 Swarm intelligence: Ants 7 Swarm intelligence: Particles 8 Machine learning 9 Artificial neural networks 10 Reinforcement learning with Q-learning
