Products related to Representation:
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Concepts in Action : Representation, Learning, and Application
This open access book is a timely contribution in presenting recent issues, approaches, and results that are not only central to the highly interdisciplinary field of concept research but also particularly important to newly emergent paradigms and challenges.The contributors present a unique, holistic picture for the understanding and use of concepts from a wide range of fields including cognitive science, linguistics, philosophy, psychology, artificial intelligence, and computer science.The chapters focus on three distinct points of view that lie at the core of concept research: representation, learning, and application.The contributions present a combination of theoretical, experimental, computational, and applied methods that appeal to students and researchers working in these fields.
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Programming Machine Learning : From Coding to Deep Learning
You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool.But where to start? It's easy to be intimidated, even as a software developer.The good news is that it doesn't have to be that hard.Master machine learning by writing code one line at a time, from simple learning programs all the way to a true deep learning system.Tackle the hard topics by breaking them down so they're easier to understand, and build your confidence by getting your hands dirty.Peel away the obscurities of machine learning, starting from scratch and going all the way to deep learning.Machine learning can be intimidating, with its reliance on math and algorithms that most programmers don't encounter in their regular work.Take a hands-on approach, writing the Python code yourself, without any libraries to obscure what's really going on.Iterate on your design, and add layers of complexity as you go.Build an image recognition application from scratch with supervised learning.Predict the future with linear regression. Dive into gradient descent, a fundamental algorithm that drives most of machine learning.Create perceptrons to classify data. Build neural networks to tackle more complex and sophisticated data sets.Train and refine those networks with backpropagation and batching.Layer the neural networks, eliminate overfitting, and add convolution to transform your neural network into a true deep learning system.Start from the beginning and code your way to machine learning mastery.What You Need: The examples in this book are written in Python, but don't worry if you don't know this language: you'll pick up all the Python you need very quickly.Apart from that, you'll only need your computer, and your code-adept brain.
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Deflating Mental Representation
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Multiple Representation Dice
Young learners will be on a roll with numbers and number sense with these Multiple Representation Dice. This set of 16 dice feature 4 different ways to represent a number, to support childrens learning of number sense. Includes 10 frames, base 10,
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Is learning programming and software development very challenging?
Learning programming and software development can be challenging for some people, as it requires logical thinking, problem-solving skills, and attention to detail. However, with dedication, practice, and the right resources, it is definitely achievable. Breaking down complex concepts into smaller, more manageable parts and seeking help from online tutorials, courses, and communities can make the learning process easier and more enjoyable. Ultimately, the level of challenge will vary depending on the individual's background, experience, and learning style.
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What is the polar representation of a Cartesian representation?
The polar representation of a Cartesian representation is a way of expressing a point in the Cartesian plane using polar coordinates. In the polar representation, a point is described by its distance from the origin (r) and the angle it makes with the positive x-axis (θ). This is in contrast to the Cartesian representation, which describes a point using its x and y coordinates. The polar representation provides a different way of understanding and visualizing points in the plane, and it can be useful in certain mathematical and scientific contexts.
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Which representation method?
The representation method that should be used depends on the specific data being analyzed and the goals of the analysis. For categorical data, bar graphs or pie charts are commonly used to show the distribution of different categories. For numerical data, histograms or box plots can be used to visualize the distribution and central tendency of the data. Scatter plots are useful for showing the relationship between two numerical variables. Ultimately, the best representation method is one that effectively communicates the key insights from the data in a clear and concise manner.
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What is the linear factor representation and the polynomial representation?
The linear factor representation of a polynomial is a way of expressing the polynomial as a product of linear factors. For example, the linear factor representation of the polynomial x^2 - 4 is (x-2)(x+2). This representation helps in finding the roots of the polynomial. The polynomial representation is the standard way of expressing a polynomial as a sum of terms, each containing a variable raised to a power. For example, the polynomial representation of x^2 - 4 is x^2 - 4. This representation helps in performing operations like addition, subtraction, multiplication, and division of polynomials.
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The Concept of Representation
Being concerned with representation, this book is about an idea, a concept, a word.It is primarily a conceptual analysis, not a historical study of the way in which representative government has evolved, nor yet an empirical investigation of the behavior of contemporary representatives or the expectations voters have about them.Yet, although the book is about a word, it is not about mere words, not merely about words.For the social philosopher, for the social scientist, words are not "mere"; they are the tools of his trade and a vital part of his subject matter.Since human beings are not merely political animals but also language-using animals, their behavior is shaped by their ideas.What they do and how they do it depends upon how they see themselves and their world, and this in turn depends upon the concepts through which they see.Learning what "representation" means and learning how to represent are intimately connected.But even beyond this, the social theorist sees the world through a network of concepts.Our words define and delimit our world in important ways, and this is particularly true of the world of human and social things. For a zoologist may capture a rare specimen and simply observe it; but who can capture an instance of representation (or of power, or of interest)?Such things, too, can be observed, but the observation always presupposes at least a rudimentary conception of what representation (or power, or interest) is, what counts as representation, where it leaves off and some other phenomenon begins.Questions about what representation is, or is like, are not fully separable from the question of what "representation" means.This book approaches the former questions by way of the latter.
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Picturebooks: Representation and Narration
This volume discusses the aesthetic and cognitive challenges of modern picturebooks from different countries, such as Denmark, France, Germany, Norway, Spain, Sweden, United Kingdom, and USA.The overarching issue concerns the mutual relationship between representation and narration by means of the picturebooks’ multimodal character.Moreover, this volume includes the main lines of debate and approaches to picturebooks by international leading researchers in the field.Topics covered are the impact of paratexts and interpictorial allusions, the relationship between artists’ books, crossover picturebooks, and picturebooks for adults, the narrative defiance of wordless picturebooks, the representation of emotions in images and text, and the depiction of hybrid characters in picturebooks.The enlargement of the picturebook corpus beyond an Anglo-American picturebook canon opens up new horizons and highlights the diverging styles and genre shifts in modern picturebooks.This tendency also demonstrates the influence of specific authors and illustrators on the appreciation of the picturebook genre, as in the case of Astrid Lindgren’s picturebooks and the picturebooks created by renowned illustrators, such as Anthony Browne, Wolf Erlbruch, Stian Hole, and Bruno Munari.This book will be the definite contribution to contemporary picturebook research for many years to come.
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Shakespeare and Queer Representation
In this engaging and accessible guidebook, Stephen Guy-Bray uses queer theory to argue that in many of Shakespeare’s works representation itself becomes queer. Shakespeare often uses representation, not just as a lens through which to tell a story, but as a textual tool in itself.Shakespeare and Queer Representation includes a thorough introduction that discusses how we can define queer representation, with each chapter developing these theories to examine works that span the entire career of Shakespeare, including his sonnets, Venus and Adonis, The Rape of Lucrece, King John, Macbeth, and Cymbeline.The book highlights the extent to which Shakespeare’s works can be seen to anticipate, and even to extend, many of the insights of the latest developments in queer theory. This thought-provoking and evocative book is an essential guide for students studying Shakespeare and Renaissance literature, gender studies, and queer literary theory.
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Knowledge Representation, Reasoning, and the Design of Intelligent Agents : The Answer-Set Programming Approach
Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks.Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems.The authors maintain a balance between mathematical analysis and practical design of intelligent agents.All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP.The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.
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Is the standard representation the same as the exponential representation?
No, the standard representation and the exponential representation are not the same. The standard representation of a number is typically in the form of a decimal or fraction, while the exponential representation is in the form of a number raised to a power. For example, the standard representation of 100 is simply "100," while the exponential representation is "10^2." These two representations convey the same value but are written in different forms.
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Which programming languages are used in software development?
There are many programming languages used in software development, including popular languages such as Java, Python, C++, JavaScript, and Ruby. Each language has its own strengths and is used for different purposes in software development. For example, Java is commonly used for building enterprise-level applications, while Python is known for its simplicity and versatility. C++ is often used for system software and game development, while JavaScript is essential for web development. Overall, the choice of programming language depends on the specific requirements of the software being developed.
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What is interest representation?
Interest representation refers to the process of advocating for the interests and concerns of a particular group or organization to policymakers, government officials, or other decision-makers. This can involve lobbying, public relations, and other forms of communication to influence policy decisions in favor of the represented group. Interest representation is a key component of democratic societies, as it allows for diverse voices and perspectives to be heard in the policymaking process. It is often carried out by professional lobbyists, advocacy groups, trade associations, and other organizations that work on behalf of their members or constituents.
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What are representation matrices?
Representation matrices are matrices that represent linear transformations or operators. They are used to represent the action of a linear transformation on a vector space. The elements of the representation matrix correspond to the coefficients of the linear combination of the basis vectors of the vector space. By using representation matrices, we can easily perform operations such as composition of linear transformations and finding the inverse of a linear transformation.
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