Download or read book Every Variable of Us written by Charles A. Bush and published by North Star Editions, Inc.. This book was released on 2022-03-01 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: After Philly teenager Alexis Duncan is injured in a gang shooting, her promising basketball career comes to a halt. At the urging of new Indian student (and crush?) Aamani, Alexis shifts her focus to the school’s STEM team in hopes of earning a college scholarship, but gains more than she could’ve imagined.
Download or read book Structures for Semantics written by Fred Landman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Formalization plays an important role in semantics. Doing semantics and following the literature requires considerable technical sophistica tion and acquaintance with quite advanced mathematical techniques and structures. But semantics isn't mathematics. These techniques and structures are tools that help us build semantic theories. Our real aim is to understand semantic phenomena and we need the technique to make our understanding of these phenomena precise. The problems in semantics are most often too hard and slippery, to completely trust our informal understanding of them. This should not be taken as an attack on informal reasoning in semantics. On the contrary, in my view, very often the essential insight in a diagnosis of what is going on in a certain semantic phenomenon takes place at the informal level. It is very easy, however, to be misled into thinking that a certain informal insight provides a satisfying analysis of a certain problem; it will often turn out that there is a fundamental unclarity about what the informal insight actually is. Formalization helps to sharpen those insights and put them to the test.
Download or read book Computer Science Theory and Applications written by Fedor V. Fomin and published by Springer. This book was released on 2018-05-24 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 13th International Computer Science Symposium in Russia, CSR 2018, held in Moscow, Russia, in May 2018. The 24 full papers presented together with 7 invited lectures were carefully reviewed and selected from 42 submissions. The papers cover a wide range of topics such as algorithms and data structures; combinatorial optimization; constraint solving; computational complexity; cryptography; combinatorics in computer science; formal languages and automata; algorithms for concurrent and distributed systems; networks; and proof theory and applications of logic to computer science.
Download or read book Discovering Modern Set Theory II Set Theoretic Tools for Every Mathematician written by Winfried Just and published by American Mathematical Soc.. This book was released on 1996 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second volume of a two-volume graduate text in set theory. The first volume covered the basics of modern set theory and was addressed primarily to beginning graduate students. The second volume is intended as a bridge between introductory set theory courses such as the first volume and advanced monographs that cover selected branches of set theory. The authors give short but rigorous introductions to set-theoretic concepts and techniques such as trees, partition calculus, cardinal invariants of the continuum, Martin's Axiom, closed unbounded and stationary sets, the Diamond Principle, and the use of elementary submodels. Great care is taken to motivate concepts and theorems presented.
Download or read book Proceedings of the National Academy of Sciences of the United States of America written by National Academy of Sciences (U.S.) and published by . This book was released on 1916 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Proceedings of the National Academy of Sciences (PNAS) publishes research reports, commentaries, reviews, colloquium papers, and actions of the Academy. PNAS is a multidisciplinary journal that covers the biological, physical, and social sciences.
Download or read book Annals of Mathematics written by and published by . This book was released on 1927 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt: Founded in 1884, Annals of Mathematics publishes research papers in pure mathematics.
Download or read book Journal of the American Society of Heating and Ventilating Engineers written by and published by . This book was released on 1928 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Principles and Practice of Constraint Programming written by Michel Rueher and published by Springer. This book was released on 2016-08-22 with total page 899 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed conference proceedings of the 22nd International Conference on Principles and Practice of Constraint Programming, CP 2016, held in Toulouse, France, in September 2016. The 63 revised regular papers presented together with 4 short papers and the abstracts of 4 invited talks were carefully reviewed and selected from 157 submissions. The scope of CP 2016 includes all aspects of computing with constraints, including theory, algorithms, environments, languages, models, systems, and applications such as decision making, resource allocation, scheduling, configuration, and planning. The papers are grouped into the following tracks: technical track; application track; computational sustainability track; CP and biology track; music track; preference, social choice, and optimization track; testing and verification track; and journal-first and sister conferences track.
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Download or read book Constraint Processing written by Rina Dechter and published by Elsevier. This book was released on 2003-05-22 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Constraint satisfaction is a simple but powerful tool. Constraints identify the impossible and reduce the realm of possibilities to effectively focus on the possible, allowing for a natural declarative formulation of what must be satisfied, without expressing how. The field of constraint reasoning has matured over the last three decades with contributions from a diverse community of researchers in artificial intelligence, databases and programming languages, operations research, management science, and applied mathematics. Today, constraint problems are used to model cognitive tasks in vision, language comprehension, default reasoning, diagnosis, scheduling, temporal and spatial reasoning. In Constraint Processing, Rina Dechter, synthesizes these contributions, along with her own significant work, to provide the first comprehensive examination of the theory that underlies constraint processing algorithms. Throughout, she focuses on fundamental tools and principles, emphasizing the representation and analysis of algorithms. Examines the basic practical aspects of each topic and then tackles more advanced issues, including current research challenges Builds the reader's understanding with definitions, examples, theory, algorithms and complexity analysis Synthesizes three decades of researchers work on constraint processing in AI, databases and programming languages, operations research, management science, and applied mathematics
Download or read book Python Machine Learning written by Railey Brandon and published by Roland Bind. This book was released on 2019-04-25 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★☆Have you come across the terms machine learning and neural networks in most articles you have recently read? Do you also want to learn how to build a machine learning model that will answer your questions within a blink of your eyes?☆★ If you responded yes to any of the above questions, you have come to the right place. Machine learning is an incredibly dense topic. It's hard to imagine condensing it into an easily readable and digestible format. However, this book aims to do exactly that. Machine learning and artificial intelligence have been used in different machines and applications to improve the user's experience. One can also use machine learning to make data analysis and predicting the output for some data sets easy. All you need to do is choose the right algorithm, train the model and test the model before you apply it on any real-world tool. It is that simple isn't it? ★★Apart from this, you will also learn more about★★ ♦ The Different Types Of Learning Algorithm That You Can Expect To Encounter ♦ The Numerous Applications Of Machine Learning And Deep Learning ♦ The Best Practices For Picking Up Neural Networks ♦ What Are The Best Languages And Libraries To Work With ♦ The Various Problems That You Can Solve With Machine Learning Algorithms ♦ And much more... Well, you can do it faster if you use Python. This language has made it easy for any user, even an amateur, to build a strong machine learning model since it has numerous directories and libraries that make it easy for one to build a model. Do you want to know how to build a machine learning model and a neural network? So, what are you waiting for? Grab a copy of this book now!
Download or read book The American Journal of Psychology written by Granville Stanley Hall and published by . This book was released on 1922 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Outlines of a Philosophy of the History of Man written by Johann Gottfried Herder and published by . This book was released on 1803 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mastering Scala written by Sufyan bin Uzayr and published by CRC Press. This book was released on 2025-07-01 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Follows a hands-on approach and offers practical lessons and tutorials related to Scala. Includes detailed tutorials meant for beginners to Scala. Discusses Scala in-depth to help build robust knowledge.
Download or read book Inductive Logic Programming written by Tamas Horváth and published by Springer. This book was released on 2003-10-24 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Inductive Logic Programming, ILP 2003, held in Szeged, Hungary in September/October 2003. The 23 revised full papers presented were carefully reviewed and selected from 53 submissions. Among the topics addressed are multirelational data mining, complexity issues, theory revision, clustering, mathematical discovery, relational reinforcement learning, multirelational learning, inductive inference, description logics, grammar systems, and inductive learning.
Download or read book Department of the Interior and Related Agencies Appropriations for 2001 U S Forest Service written by United States. Congress. House. Committee on Appropriations. Subcommittee on Department of the Interior and Related Agencies and published by . This book was released on 2000 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hands On Ensemble Learning with R written by Prabhanjan Narayanachar Tattar and published by Packt Publishing Ltd. This book was released on 2018-07-27 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore powerful R packages to create predictive models using ensemble methods Key Features Implement machine learning algorithms to build ensemble-efficient models Explore powerful R packages to create predictive models using ensemble methods Learn to build ensemble models on large datasets using a practical approach Book Description Ensemble techniques are used for combining two or more similar or dissimilar machine learning algorithms to create a stronger model. Such a model delivers superior prediction power and can give your datasets a boost in accuracy. Hands-On Ensemble Learning with R begins with the important statistical resampling methods. You will then walk through the central trilogy of ensemble techniques – bagging, random forest, and boosting – then you'll learn how they can be used to provide greater accuracy on large datasets using popular R packages. You will learn how to combine model predictions using different machine learning algorithms to build ensemble models. In addition to this, you will explore how to improve the performance of your ensemble models. By the end of this book, you will have learned how machine learning algorithms can be combined to reduce common problems and build simple efficient ensemble models with the help of real-world examples. What you will learn Carry out an essential review of re-sampling methods, bootstrap, and jackknife Explore the key ensemble methods: bagging, random forests, and boosting Use multiple algorithms to make strong predictive models Enjoy a comprehensive treatment of boosting methods Supplement methods with statistical tests, such as ROC Walk through data structures in classification, regression, survival, and time series data Use the supplied R code to implement ensemble methods Learn stacking method to combine heterogeneous machine learning models Who this book is for This book is for you if you are a data scientist or machine learning developer who wants to implement machine learning techniques by building ensemble models with the power of R. You will learn how to combine different machine learning algorithms to perform efficient data processing. Basic knowledge of machine learning techniques and programming knowledge of R would be an added advantage.
