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Book Synopsis Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky by : Ning Wang
Download or read book Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky written by Ning Wang and published by Springer Nature. This book was released on 2023-06-29 with total page 855 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes poster papers and late breaking results presented during the 24th International Conference on Artificial Intelligence in Education, AIED 2023, Tokyo, Japan, July 3–7, 2023. The 65 poster papers presented were carefully reviewed and selected from 311 submissions. This set of posters was complemented with the other poster contributions submitted for the Poster and Late Breaking results track of the AIED 2023 conference.
Book Synopsis Foundations of Data Science by : Avrim Blum
Download or read book Foundations of Data Science written by Avrim Blum and published by Cambridge University Press. This book was released on 2020-01-23 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Addison-Wesley Mathematics [grade 4] by :
Download or read book Addison-Wesley Mathematics [grade 4] written by and published by . This book was released on 1987 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Python for Data Analysis by : Wes McKinney
Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Download or read book Doing AI written by Richard Heimann and published by BenBella Books. This book was released on 2021-12-14 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) has captured our imaginations—and become a distraction. Too many leaders embrace the oversized narratives of artificial minds outpacing human intelligence and lose sight of the original problems they were meant to solve. When businesses try to “do AI,” they place an abstract solution before problems and customers without fully considering whether it is wise, whether the hype is true, or how AI will impact their organization in the long term. Often absent is sound reasoning for why they should go down this path in the first place. Doing AI explores AI for what it actually is—and what it is not— and the problems it can truly solve. In these pages, author Richard Heimann unravels the tricky relationship between problems and high-tech solutions, exploring the pitfalls in solution-centric thinking and explaining how businesses should rethink AI in a way that aligns with their cultures, goals, and values. As the Chief AI Officer at Cybraics Inc., Richard Heimann knows from experience that AI-specific strategies are often bad for business. Doing AI is his comprehensive guide that will help readers understand AI, avoid common pitfalls, and identify beneficial applications for their companies. This book is a must-read for anyone looking for clarity and practical guidance for identifying problems and effectively solving them, rather than getting sidetracked by a shiny new “solution” that doesn’t solve anything.
Book Synopsis Big Data Science in Finance by : Irene Aldridge
Download or read book Big Data Science in Finance written by Irene Aldridge and published by John Wiley & Sons. This book was released on 2021-01-08 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.
Book Synopsis Data Preparation for Data Mining by : Dorian Pyle
Download or read book Data Preparation for Data Mining written by Dorian Pyle and published by Morgan Kaufmann. This book was released on 1999-03-22 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the importance of clean, well-structured data as the first step to successful data mining. It shows how data should be prepared prior to mining in order to maximize mining performance.
Book Synopsis Synthetic Data for Deep Learning by : Sergey I. Nikolenko
Download or read book Synthetic Data for Deep Learning written by Sergey I. Nikolenko and published by Springer Nature. This book was released on 2021-06-26 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come. The book can also serve as an introduction to several other important subfields of machine learning that are seldom touched upon in other books. Machine learning as a discipline would not be possible without the inner workings of optimization at hand. The book includes the necessary sinews of optimization though the crux of the discussion centers on the increasingly popular tool for training deep learning models, namely synthetic data. It is expected that the field of synthetic data will undergo exponential growth in the near future. This book serves as a comprehensive survey of the field. In the simplest case, synthetic data refers to computer-generated graphics used to train computer vision models. There are many more facets of synthetic data to consider. In the section on basic computer vision, the book discusses fundamental computer vision problems, both low-level (e.g., optical flow estimation) and high-level (e.g., object detection and semantic segmentation), synthetic environments and datasets for outdoor and urban scenes (autonomous driving), indoor scenes (indoor navigation), aerial navigation, and simulation environments for robotics. Additionally, it touches upon applications of synthetic data outside computer vision (in neural programming, bioinformatics, NLP, and more). It also surveys the work on improving synthetic data development and alternative ways to produce it such as GANs. The book introduces and reviews several different approaches to synthetic data in various domains of machine learning, most notably the following fields: domain adaptation for making synthetic data more realistic and/or adapting the models to be trained on synthetic data and differential privacy for generating synthetic data with privacy guarantees. This discussion is accompanied by an introduction into generative adversarial networks (GAN) and an introduction to differential privacy.
Book Synopsis The Data Science Design Manual by : Steven S. Skiena
Download or read book The Data Science Design Manual written by Steven S. Skiena and published by Springer. This book was released on 2017-07-01 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)
Book Synopsis MoneyBall Medicine by : Harry Glorikian
Download or read book MoneyBall Medicine written by Harry Glorikian and published by Taylor & Francis. This book was released on 2017-11-20 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can a smartwatch help patients with diabetes manage their disease? Why can’t patients find out prices for surgeries and other procedures before they happen? How can researchers speed up the decade-long process of drug development? How will "Precision Medicine" impact patient care outside of cancer? What can doctors, hospitals, and health systems do to ensure they are maximizing high-value care? How can healthcare entrepreneurs find success in this data-driven market? A revolution is transforming the $10 trillion healthcare landscape, promising greater transparency, improved efficiency, and new ways of delivering care. This new landscape presents tremendous opportunity for those who are ready to embrace the data-driven reality. Having the right data and knowing how to use it will be the key to success in the healthcare market in the future. We are already starting to see the impacts in drug development, precision medicine, and how patients with rare diseases are diagnosed and treated. Startups are launched every week to fill an unmet need and address the current problems in the healthcare system. Digital devices and artificial intelligence are helping doctors do their jobs faster and with more accuracy. MoneyBall Medicine: Thriving in the New Data-Driven Healthcare Market, which includes interviews with dozens of healthcare leaders, describes the business challenges and opportunities arising for those working in one of the most vibrant sectors of the world’s economy. Doctors, hospital administrators, health information technology directors, and entrepreneurs need to adapt to the changes effecting healthcare today in order to succeed in the new, cost-conscious and value-based environment of the future. The authors map out many of the changes taking place, describe how they are impacting everyone from patients to researchers to insurers, and outline some predictions for the healthcare industry in the years to come.
Book Synopsis Data Analysis Using SQL and Excel by : Gordon S. Linoff
Download or read book Data Analysis Using SQL and Excel written by Gordon S. Linoff and published by John Wiley & Sons. This book was released on 2010-09-16 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful business analysis requires you to effectively transform data into actionable information. This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what the results should look like.
Download or read book Lean Analytics written by Alistair Croll and published by "O'Reilly Media, Inc.". This book was released on 2024-02-23 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you're a startup founder trying to disrupt an industry or an entrepreneur trying to provoke change from within, your biggest challenge is creating a product people actually want. Lean Analytics steers you in the right direction. This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without. Understand Lean Startup, analytics fundamentals, and the data-driven mindset Look at six sample business models and how they map to new ventures of all sizes Find the One Metric That Matters to you Learn how to draw a line in the sand, so you'll know it's time to move forward Apply Lean Analytics principles to large enterprises and established products
Book Synopsis Georgetown Journal of International Affairs, Summer/Fall 2014 by : Medha Raj
Download or read book Georgetown Journal of International Affairs, Summer/Fall 2014 written by Medha Raj and published by Georgetown University Press. This book was released on 2014-09-08 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This issue of the Georgetown Journal of International Affairs focuses on the topic of "Destabilizing Demographics," exploring the opportunities and challenges presented by dynamic population patterns and structures. Demographic shifts affect multiple facets of international affairs, impacting economies, modifying politics, and reshaping the fabric of our societies. These changes could have catastrophic international consequences if ignored or evaded. This edition concludes with articles regarding decidedly twenty-first century concerns: communication, integration, and globalization. The Georgetown Journal of International Affairs is the official publication of the Edmund A. Walsh School of Foreign Service at Georgetown University. Each issue of the journal provides readers with a diverse array of timely, peer-reviewed content penned by top policymakers, business leaders, and academic luminaries.
Book Synopsis Problem-Solving Through Problems by : Loren C. Larson
Download or read book Problem-Solving Through Problems written by Loren C. Larson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a practical anthology of some of the best elementary problems in different branches of mathematics. Arranged by subject, the problems highlight the most common problem-solving techniques encountered in undergraduate mathematics. This book teaches the important principles and broad strategies for coping with the experience of solving problems. It has been found very helpful for students preparing for the Putnam exam.
Book Synopsis Creative Thinking And Problem Solving by : John Fabian
Download or read book Creative Thinking And Problem Solving written by John Fabian and published by CRC Press. This book was released on 2018-01-10 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical new book for scientists, engineers, project leaders, and others working in the technical fields. The book adds depth, "how-to", and success to your creative thinking and problem solving. This book will allow you to sharpen your creative edge, giving you better problem solving skills. Whether you are a scientist working on breakthrough research, an engineer on the forefront of product development, or a project manager forging teams to reach and exceed goals, this new book gives you the fundamentals and advanced techniques of creative thinking to break new ground and reach higher levels of excellence.
Book Synopsis Simplifying Data Engineering and Analytics with Delta by : Anindita Mahapatra
Download or read book Simplifying Data Engineering and Analytics with Delta written by Anindita Mahapatra and published by Packt Publishing Ltd. This book was released on 2022-07-29 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore how Delta brings reliability, performance, and governance to your data lake and all the AI and BI use cases built on top of it Key Features • Learn Delta’s core concepts and features as well as what makes it a perfect match for data engineering and analysis • Solve business challenges of different industry verticals using a scenario-based approach • Make optimal choices by understanding the various tradeoffs provided by Delta Book Description Delta helps you generate reliable insights at scale and simplifies architecture around data pipelines, allowing you to focus primarily on refining the use cases being worked on. This is especially important when you consider that existing architecture is frequently reused for new use cases. In this book, you'll learn about the principles of distributed computing, data modeling techniques, and big data design patterns and templates that help solve end-to-end data flow problems for common scenarios and are reusable across use cases and industry verticals. You'll also learn how to recover from errors and the best practices around handling structured, semi-structured, and unstructured data using Delta. After that, you'll get to grips with features such as ACID transactions on big data, disciplined schema evolution, time travel to help rewind a dataset to a different time or version, and unified batch and streaming capabilities that will help you build agile and robust data products. By the end of this Delta book, you'll be able to use Delta as the foundational block for creating analytics-ready data that fuels all AI/BI use cases. What you will learn • Explore the key challenges of traditional data lakes • Appreciate the unique features of Delta that come out of the box • Address reliability, performance, and governance concerns using Delta • Analyze the open data format for an extensible and pluggable architecture • Handle multiple use cases to support BI, AI, streaming, and data discovery • Discover how common data and machine learning design patterns are executed on Delta • Build and deploy data and machine learning pipelines at scale using Delta Who this book is for Data engineers, data scientists, ML practitioners, BI analysts, or anyone in the data domain working with big data will be able to put their knowledge to work with this practical guide to executing pipelines and supporting diverse use cases using the Delta protocol. Basic knowledge of SQL, Python programming, and Spark is required to get the most out of this book.
Book Synopsis New Horizons of Parallel and Distributed Computing by : Minyi Guo
Download or read book New Horizons of Parallel and Distributed Computing written by Minyi Guo and published by Springer Science & Business Media. This book was released on 2006-01-27 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parallel and distributed computing is one of the foremost technologies for shaping future research and development activities in academia and industry. Hyperthreading in Intel processors, hypertransport links in next generation AMD processors, multicore silicon in today’s high-end microprocessors, and emerging cluster and grid computing have moved parallel/distributed computing into the mainstream of computing. New Horizons of Parallel and Distributed Computing is a collection of self-contained chapters written by pioneering researchers to provide solutions for newly emerging problems in this field. This volume will not only provide novel ideas, work in progress and state-of-the-art techniques in the field, but will also stimulate future research activities in the area of parallel and distributed computing with applications. New Horizons of Parallel and Distributed Computing is intended for industry researchers and developers, as well as for academic researchers and advanced-level students in computer science and electrical engineering. A valuable reference work, it is also suitable as a textbook.
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