“…It assumes knowledge only of elementary algebra and elementary statistics. Symbols and terminology are kept at a basic level so that the eventual and hoped for transfer to a more advanced text will be accomplished as easily as possible. …”

Tabla de Contenidos: “…IntroductionGraphics AreasMajor ApplicationsGraphics APIsGraphics PipelineNumerical IssuesEfficiencyDesigning and Coding Graphics ProgramsMiscellaneous MathSets and MappingsSolving Quadratic EquationsTrigonometryVectorsCurves and SurfacesLinear InterpolationTrianglesRaster ImagesRaster DevicesImages, Pixels, and GeometryRGB ColorAlpha CompositingRay TracingThe Basic Ray-Tracing AlgorithmPerspectiveComputing Viewing RaysRay-Object IntersectionShadingA Ray-Tracing ProgramShadowsIdeal Specular ReflectionHistorical NotesLinear AlgebraDeterminantsMatricesComputing with Matrices and DeterminantsEigenvalues and Matrix DiagonalizationTransformation Matrices2D Linear Transformations3D Linear TransformationsTranslation and Affine TransformationsInverses of Transformation MatricesCoordinate TransformationsViewingViewing TransformationsProjective TransformationsPerspective ProjectionSome Properties of the Perspective TransformField-of-ViewThe Graphics PipelineRasterizationOperations Before and After RasterizationSimple AntialiasingCulling Primitives for EfficiencySignal ProcessingDigital Audio: Sampling in 1DConvolutionConvolution FiltersSignal Processing for ImagesSampling TheorySurface ShadingDiffuse ShadingPhong ShadingArtistic ShadingTexture MappingLooking Up Texture ValuesTexture Coordinate FunctionsAntialiasing Texture LookupsApplications of Texture MappingProcedural 3D TexturesData Structures for GraphicsTriangle MeshesScene GraphsSpatial Data StructuresBSP Trees for VisibilityTiling Multidimensional ArraysMore Ray TracingTransparency and RefractionInstancingConstructive Solid GeometryDistribution Ray TracingSamplingIntegrationContinuous ProbabilityMonte Carlo IntegrationChoosing Random PointsCurvesCurvesCurve PropertiesPolynomial PiecesPutting Pieces TogetherCubicsApproximating CurvesSummaryComputer AnimationPrinciples of AnimationKeyframingDeformationsCharacter AnimationPhysics-Based AnimationProcedural TechniquesGroups of ObjectsUsing Graphics HardwareHardware OverviewWhat Is Graphics HardwareHeterogeneous MultiprocessingGraphics Hardware Programming: Buffers, State, and ShadersState MachineBasic OpenGL Application LayoutGeometryA First Look at ShadersVertex Buffer ObjectsVertex Array ObjectsTransformation MatricesShading with Per-Vertex AttributesShading in the Fragment ProcessorMeshes and InstancingTexture ObjectsObject-Oriented Design for Graphics Hardware ProgrammingContinued LearningLightRadiometryTransport EquationPhotometryColorColorimetryColor SpacesChromatic AdaptationColor AppearanceVisual PerceptionVision ScienceVisual SensitivitySpatial VisionObjects, Locations, and EventsPicture PerceptionTone ReproductionClassificationDynamic RangeColorImage FormationFrequency-Based OperatorsGradient-Domain OperatorsSpatial OperatorsDivisionSigmoidsOther ApproachesNight TonemappingDiscussionImplicit ModelingImplicit Functions, Skeletal Primitives, and Summation BlendingRenderingSpace PartitioningMore on BlendingConstructive Solid GeometryWarpingPrecise Contact ModelingThe Blob TreeInteractive Implicit Modeling SystemsGlobal IlluminationParticle Tracing for Lambertian ScenesPath TracingAccurate Direct LightingReflection ModelsReal-World MaterialsImplementing Reflection ModelsSpecular Reflection ModelsSmooth-Layered ModelRough-Layered ModelComputer Graphics in GamesPlatformsLimited ResourcesOptimization TechniquesGame TypesThe Game Production ProcessVisualizationBackgroundData TypesHuman-Centered Design ProcessVisual Encoding PrinciplesInteraction PrinciplesComposite and Adjacent ViewsData ReductionExamples…”

“…You’ll learn how to analyze data by applying concepts of statistics, probability theory, and linear algebra. In this new edition, both R and Python are used to demonstrate these analyses. …”

“…Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and a rustya calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. …”

“…The book also explores the relationships between the Lund model and other models based on field theory (the Schwinger model, S-matrix models, light-cone algebra physics and variations of the parton model), and models based on statistical mechanics (the Feynman-Wilson gas, scaling, iterative cascade models). …”

Tabla de Contenidos: “…Fundamentals of Mathematics -- Arithmetic -- Numbers -- Addition and Subtraction -- Multiplication -- Division -- Fractions -- Decimals -- Percentage -- Ratio and Proportion -- Powers and Roots -- Scientific Notation -- Algebra -- Introduction -- Equations -- Positive and Negative Numbers -- Algebraic Addition -- Algebraic Subtraction -- Use of Parentheses -- Multiplication -- Division -- Order of Operations -- Solution of Problems -- Geometry -- Definitions -- Lines -- Angles -- Shapes -- Formulas -- Geometric Constructions -- Trigonometry -- Trigonometric Functions -- Solution of Right Triangles -- Changes in Values of Functions -- Functions of Particular Angles -- Alternative Number Systems -- Charts and Graphs -- Graphs -- Graphs of Mathematical Functions -- Review Questions -- 2. …”

Tabla de Contenidos: “…-- Nvidia GPU support optimized -- Introducing TensorFlow Lite -- Eager execution -- Optimized Accelerated Linear Algebra (XLA) -- Installing and configuring TensorFlow -- TensorFlow computational graph -- TensorFlow code structure -- Eager execution with TensorFlow -- Data model in TensorFlow -- Tensor -- Rank and shape -- Data type -- Variables -- Fetches -- Feeds and placeholders -- Visualizing computations through TensorBoard -- How does TensorBoard work? …”

Tabla de Contenidos: “…Ridge regression -- LASSO regression -- Data clustering -- The K-means algorithm -- K-means implementation with Spark ML -- Data dimensionality reduction -- Singular value decomposition -- Matrix theory and linear algebra overview -- The important properties of singular value decomposition -- SVD with Spark ML -- The principal component analysis method -- The PCA algorithm using SVD -- Implementing SVD with Spark ML -- Content-based recommendation systems -- Frequently asked questions -- Summary -- Chapter 4: Neural Network for Big Data -- Fundamentals of neural networks and artificial neural networks -- Perceptron and linear models -- Component notations of the neural network -- Mathematical representation of the simple perceptron model -- Activation functions -- Sigmoid function -- Tanh function -- ReLu -- Nonlinearities model -- Feed-forward neural networks -- Gradient descent and backpropagation -- Gradient descent pseudocode -- Backpropagation model -- Overfitting -- Recurrent neural networks -- The need for RNNs -- Structure of an RNN -- Training an RNN -- Frequently asked questions -- Summary -- Chapter 5: Deep Big Data Analytics -- Deep learning basics and the building blocks -- Gradient-based learning -- Backpropagation -- Non-linearities -- Dropout -- Building data preparation pipelines -- Practical approach to implementing neural net architectures -- Hyperparameter tuning -- Learning rate -- Number of training iterations -- Number of hidden units -- Number of epochs -- Experimenting with hyperparameters with Deeplearning4j -- Distributed computing -- Distributed deep learning -- DL4J and Spark -- API overview -- TensorFlow -- Keras -- Frequently asked questions -- Summary -- Chapter 6: Natural Language Processing -- Natural language processing basics -- Text preprocessing -- Removing stop words -- Stemming -- Porter stemming…”

Tabla de Contenidos: “…Basic questions for data exploration -- Dataset 1 - Yelp -- Dataframes -- Series -- Exploration tips for qualitative data -- Dataset 2 - titanic -- Summary -- Chapter 4: Basic Mathematics -- Mathematics as a discipline -- Basic symbols and terminology -- Vectors and matrices -- Quick exercises -- Answers -- Arithmetic symbols -- Summation -- Proportional -- Dot product -- Graphs -- Logarithms/exponents -- Set theory -- Linear algebra -- Matrix multiplication -- How to multiply matrices -- Summary -- Chapter 5: Impossible or Improbable - A Gentle Introduction to Probability -- Basic definitions -- Probability -- Bayesian versus Frequentist -- Frequentist approach -- The law of large numbers -- Compound events -- Conditional probability -- The rules of probability -- The addition rule -- Mutual exclusivity -- The multiplication rule -- Independence -- Complementary events -- A bit deeper -- Summary -- Chapter 6: Advanced Probability -- Collectively exhaustive events -- Bayesian ideas revisited -- Bayes theorem -- More applications of Bayes theorem -- Example - Titanic -- Example - medical studies -- Random variables -- Discrete random variables -- Types of discrete random variables -- Summary -- Chapter 7: Basic Statistics -- What are statistics? …”

Tabla de Contenidos: “…Cover -- Contents -- List of Figures -- List of Tables -- Preface -- Acknowledgements -- Chapter 1: Preliminary Background -- Theme of the Book -- Course Contents -- Sources for More Detailed Study -- Directions for Using the Book -- Expected Background -- Preliminary Test -- Prerequisite Problem Sets* -- Problem set 1 -- Problem set 2 -- Problem set 3 -- Problem set 4 -- Problem set 5 -- Problem set 6 -- Chapter 2: Matrices and Linear Transformations -- Matrices -- Geometry and Algebra -- Linear Transformations -- Matrix Terminology -- Exercises -- Chapter 3: Operational Fundamentals of Linear Algebra -- Range and Null Space: Rank and Nullity -- Basis -- Change of Basis -- Elementary Transformations -- Exercises -- Chapter 4: Systems of Linear Equations -- Nature of Solutions -- Basic Idea of Solution Methodology -- Homogeneous Systems -- Pivoting -- Partitioning and Block Operations -- Exercises -- Chapter 5: Gauss Elimination Family of Methods -- Gauss-Jordan Elimination -- Gaussian Elimination with Back-Substitution -- LU Decomposition -- Exercises -- Chapter 6: Special Systems and Special Methods -- Quadratic Forms, Symmetry and Positive Definiteness -- Cholesky Decomposition -- Sparse Systems* -- Exercises -- Chapter 7: Numerical Aspects in Linear Systems -- Norms and Condition Numbers -- Ill-conditioning and Sensitivity -- Rectangular Systems -- Singularity-Robust Solutions -- Iterative Methods -- Exercises -- Chapter 8: Eigenvalues and Eigenvectors -- Eigenvalue Problem -- Generalized Eigenvalue Problem -- Some Basic Theoretical Results -- Eigenvalues of transpose -- Diagonal and block diagonal matrices -- Triangular and block triangular matrices -- Shift theorem -- Deflation -- Eigenspace -- Similarity transformation -- Power Method -- Exercises -- Chapter 9: Diagonalization and Similarity Transformations -- Diagonalizability…”

Tabla de Contenidos: “…9.3.1 Sequentialisation rule -- 9.3.2 Tensor product of quantum predicates -- 9.3.3 Separable quantum predicates -- 9.3.4 Entangled quantum predicates -- 9.3.5 Auxiliary variables -- 9.3.6 Transferring separable predicates to entangled -- 9.3.7 Completeness of the auxiliary variables method -- 9.3.8 Completeness of the entanglement transformation method -- 9.4 Syntax of parallel quantum programs with shared variables -- 9.5 Semantics of parallel quantum programs with shared variables -- 9.6 Reasoning about parallel quantum programs with shared variables -- 9.6.1 A rule for component quantum programs -- 9.6.2 Proof outlines -- 9.6.3 Interference freedom -- 9.6.4 A rule for parallel composition of quantum programs with shared variables -- 9.7 Discussions -- 9.8 Bibliographic remarks and further readings -- 10 Distributed quantum programs -- 10.1 Quantum process algebra qCCS -- 10.1.1 Syntax -- 10.1.2 Operational semantics -- 10.1.3 Examples -- 10.1.4 Properties of transitions -- 10.2 Bisimulations between quantum processes -- 10.2.1 Basic definitions -- 10.2.2 Algebraic laws -- 10.2.3 Congruence -- 10.2.4 Recursion -- 10.2.5 Strong reduction-bisimilarity -- 10.2.6 Weak bisimulations -- 10.3 Approximate bisimulations between quantum processes -- 10.4 Adding classical variables -- 10.4.1 Syntax -- 10.4.2 Operational semantics -- 10.4.3 Examples -- 10.4.4 Bisimulations -- 10.5 Bibliographic remarks and further readings -- V Quantum control flows -- 11 Quantum case statements -- 11.1 Case statements: from classical to quantum -- 11.2 QuGCL: a language with quantum case statements -- 11.3 Guarded compositions of quantum operations -- 11.3.1 Guarded composition of unitary operators -- 11.3.2 Operator-valued functions -- 11.3.3 Guarded composition of operator-valued functions -- 11.3.4 Guarded composition of quantum operations…”

Tabla de Contenidos: “…-- 3.1 Quaternions are extended complex numbers -- 3.2 Quaternions are two-by-two matrices -- 3.3 Quaternions are a complexified pair of complex numbers -- 3.4 Quaternions are the group SU(2) -- 3.5 Quaternion actions can be realized in complex projective space -- 3.6 Quaternions are one of the four normed division algebras -- 3.7 Quaternions are a special case of Clifford algebras -- 3.8 Quaternions are points on the 3-sphere S3 -- 3.9 Synopsis -- 4 What is quaternion visualization? …”

Tabla de Contenidos: “…Cálculo avanzado para ingeniría: teoría, problemas resueltos y aplicaciones; Página Legal ; Índice general; Prólogo; 1 Álgebra lineal; 1.1. Abreviaciones; 1.2. Matrices. …”
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Tabla de Contenidos: “…Concepto de claves en el modelo relacional -- 4. Nociones del álgebra relacional -- 5. Nociones de cálculo relacional de tuplas para poder resolver ejercicios prácticos básicos -- 6. …”

Tabla de Contenidos: “….) -- UNIDAD I FÍSICA -- MODELOS, TEORÍA Y LEYES -- EL MÉTODO CIENTÍFICO -- CLASIFICACIÓN DE LA FÍSICA -- DEFINICIÓN DE TEMAS DE LA FÍSICA -- ANÁLISIS DIMENSIONAL -- MAGNITUDES FÍSICAS -- CARACTERÍSTICAS DE UN VECTOR -- MÉTODOS GRÁFICOS -- EJERCICIOS DE MAGNITUDES -- CONCEPTO DE MASA, FUERZA U PESO -- UNIDAD II ALGEBRA VECTORIAL -- DEFINICIÓN -- FUERZAS EN CONTACTO Y A DISTANCIA -- MÉTODOS ANALÍTICOS -- PROBLEMAS RESUELTOS DE ANÁLISIS VECTORIAL -- PROBLEMAS PROPUESTOS DE ANÁLISIS VECTORIAL -- DEFINICIÓN DE PRODUCTO ESCALAR DE DOS VECTORES -- PRODUCTO VECTORIAL DE DOS VECTORES -- MOMENTO O TORCA -- CONDICIONES DE EQUILIBRIO -- PROBLEMAS RESUELTOS DE CONDICIONES DE MOMENTOS -- PROBLEMAS DE TENSIONES -- PROBLEMAS DE TENSIONES Y CONDICIONES DE (...) -- PROBLEMAS PROPUESTOS DE MOMENTOS, TENSIONES (...) -- CENTRO DE GRAVEDAD -- ECUACIONES DE DINÁMICA DE ROTACIÓN -- IMPULSO ANGULAR -- CENTROIDE -- PROBLEMAS RESUELTOS DE CENTROIDES -- PROBLEMAS PROPUESTOS DE CENTROIDES -- EXÁMENES PARA 1o DEPARTAMENTAL EXAMEN 1 -- EXÁMENES PARA 2o DEPARTAMENTAL EXAMEN 2 -- UNIDAD III CINEMÁTICA -- DEFINICIÓN -- MOVIMIENTO RECTILÍNEO UNIFORME MRU -- PROBLEMAS CON SOLUCIÓN DE MRU -- PROBLEMAS PROPUESTOS DE MRU -- EL MOVIMIENTO VARIADO O UNIFORMEMENTE VARIADO -- PROBLEMAS CON SOLUCIÓN DE MRUV -- PROBLEMAS PROPUESTOS DE MRUV -- CAÍDA LIBRE -- PROBLEMAS RESUELTOS DE CL -- PROBLEMAS PROPUESTOS DE CL -- TIRO VERTICAL -- PROBLEMAS RESUELTOS DE TV -- PROBLEMAS PROPUESTOS DE TV -- TIRO HORIZONTAL…”

Tabla de Contenidos: “…Preface""; ""PART ONE: THE BLANDYKE PAPERS""; ""1 The Form of Mathematical Inference""; ""1 Vis Cogitativa and Concrete Inference""; ""2 Universals of Sense, Generic Image, and Axioms""; ""3 Vis Cogitativa and an Example of Concrete Inference in Geometry""; ""4 Vis Cogitativa and an Example of Concrete Inference in Algebra""; ""Appendix""; ""2 The Syllogism""; ""1 Types of Inference""; ""2 Predication, Logical Whole and Part, and the Hypothetical Argument in Inference""; ""3 Syllogism and the Reduction to the Hypothetical""; ""4 Concluding Reflections""…”
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Tabla de Contenidos: “…Using Computer Tools for Modeling and Simulation Seeing the Big Picture; Chapter 2: Brushing Up on Math; Revealing Unknowns with Algebra; Making Nice Signal Models with Trig Functions; Manipulating Numbers: Essential Complex Arithmetic; Catching Up with Calculus; Finding Polynomial Roots; Chapter 3: Continuous-Time Signals and Systems; Considering Signal Types; Getting Hip to Signal Classifications; Transforming Simple Signals; Checking Out System Properties; Choosing Linear and Time-Invariant Systems; Chapter 4: Discrete-Time Signals and Systems; Exploring Signal Types…”

Tabla de Contenidos: “…OPERACIONES CON VECTORES. ALGEBRA VECTORIAL…”

Tabla de Contenidos: “…N and Problems of Convergence of Fourier Series of Functions Which Equal Zero on Some Set -- Sidon Type Inequalities for Wavelets -- Almansi Decomposition for Dunkl-Helmholtz Operators -- An Uncertainty Principle for Operators -- Uncertainty Principle for Clifford Geometric Algebras Cl n,0, n = 3 (mod 4) Based on Clifford Fourier Transform -- Orthogonal Wavelet Vectors in a Hilbert Space -- Operator Frames for -- On the Stability of Multi-wavelet Frames -- Biorthogonal Wavelets Associated with Two-Dimensional Interpolatory Function -- Parameterization of Orthogonal Filter Bank with Linear Phase -- On Multivariate Wavelets with Trigonometric Vanishing Moments -- Directional Wavelet Analysis with Fourier-Type Bases for Image Processing -- Unitary Systems and Wavelet Sets -- Clifford Analysis and the Continuous Spherical Wavelet Transform -- Clifford-Jacobi Polynomials and the Associated Continuous Wavelet Transform in Euclidean Space -- Wavelet Leaders in Multifractal Analysis -- Application of Fast Wavelet Transformation in Parametric System Identification -- Image Denoising by a Novel Digital Curvelet Reconstruction Algorithm -- Condition Number for Under-Determined Toeplitz Systems -- Powell-Sabin Spline Prewavelets on the Hexagonal Lattice -- Time-Frequency Aspects of Nonlinear Fourier Atoms -- Mono-components for Signal Decomposition -- Signal-Adaptive Aeroelastic Flight Data Analysis with HHT -- An Adaptive Data Analysis Method for Nonlinear and Nonstationary Time Series: The Empirical Mode Decomposition and Hilbert Spectral Analysis -- Wavelet Applications -- Transfer Colors from CVHD to MRI Based on Wavelets Transform -- Medical Image Fusion by Multi-resolution Analysis of Wavelets Transform -- Salient Building Detection from a Single Nature Image via Wavelet Decomposition -- SAR Images Despeckling via Bayesian Fuzzy Shrinkage Based on Stationary Wavelet Transform -- Super-Resolution Reconstruction Using Haar Wavelet Estimation -- The Design of Hilbert Transform Pairs in Dual-Tree Complex Wavelet Transform -- Supervised Learning Using Characteristic Generalized Gaussian Density and Its Application to Chinese Materia Medica Identification -- A Novel Algorithm of Singular Points Detection for Fingerprint Images -- Wavelet Receiver: A New Receiver Scheme for Doubly-Selective Channels -- Face Retrieval with Relevance Feedback Using Lifting Wavelets Features -- High-Resolution Image Reconstruction Using Wavelet Lifting Scheme -- Mulitiresolution Spatial Data Compression Using Lifting Scheme -- Ridgelet Transform as a Feature Extraction Method in Remote Sensing Image Recognition -- Analysis of Frequency Spectrum for Geometric Modeling in Digital Geometry -- Detection of Spindles in Sleep EEGs Using a Novel Algorithm Based on the Hilbert-Huang Transform -- A Wavelet-Domain Hidden Markov Tree Model with Localized Parameters for Image Denoising…”

Tabla de Contenidos: “…Cover -- Btec First Engineering -- Copyright Page -- Contents -- Preface -- Unit 1: Working Safely and Effectively in Engineering -- 1.1 Regulations and Safety -- 1.2 Working Efficiently and Effectively in Engineering -- Review Questions -- Unit 2: Interpreting and Using Engineering Information -- 2.1 Interpreting Drawings and Documentation -- Review Questions -- Unit 3: Mathematics for Engineering Technicians -- 3.1 Arithmetic, Algebra and Graphical Methods -- 3.2 Mensuration and Trigonometry -- Review Questions -- Unit 4: Applied Electrical and Mechanical Science -- 4.1 Electrical Science -- 4.2 Mechanical Science -- Review Questions -- Unit 7: Electronic Devices and Communication Applications -- 5.1 Signals and Units of Measurement -- 5.2 Electronic Components and Devices -- 5.3 Analogue and Digital Circuits -- 5.4 Communication Systems and Data Transmission -- Questions -- Unit 8: Selecting Engineering Materials -- 6.1 Introducing Engineering Materials -- 6.2 Properties of Materials -- 6.3 Classes of Material -- 6.4 Ferrous Metals -- 6.5 Non-ferrous Metals -- 6.6 Non-metals -- 6.7 Composites -- 6.8 Coding and Identifying Materials -- Review Questions -- Unit 10: Computer Aided Drawing Techniques -- 7.1 Introducing Computer Aided Drawing, Design and Manufacture -- 7.2 2d Cad -- 7.3 3d Cad -- 7.4 Drawing Standards and Conventions -- 7.5 Producing and Storing Engineering Drawings -- 7.6 Drawing Projections -- 7.7 Getting Started with Cad -- 7.8 Getting Started with Autocad -- Review Questions -- Unit 19: Electronic Circuit Construction -- 8.1 Safety -- 8.2 Electronic Components -- 8.3 Circuit Diagrams -- 8.5 Component Colour Codes and Markings -- 8.6 Cables and Hardware -- 8.7 Logic Circuits -- 8.8 Circuit Construction -- 8.9 Test Equipment and Measurements -- Review Questions -- Appendix 1. …”