“… - Las aplicaciones de los números complejos en geometría y en electricidad - Las técnicas matriciales para el álgebra lineal y la electricidad - Las finanzas: cálculo de rentabilidad, cálculo de mensualidad, cálculos actuariales, etc…”
Acceso con credenciales UPSA.

“…El trabajo describe las facilidades que ofrece un sistema algebraico computarizado cuyo marco de referencia es la enseñanza de la aritmética y el álgebra antes de la aparición de esa tecnología; presenta una breve discusión del referente teórico en que se sustenta el estudio y el método empleado de recolección y análisis de datos; concluye con una discusión de los resultados…”
Acceso con credenciales UPSA

Tabla de Contenidos: “…EL LENGUAJE DE LAS MATEMÁTICAS -- PÁGINA LEGAL -- ÍNDICE -- EL NACIMIENTO DEL ÁLGEBRA -- ¿CÓMO USAMOS LOS SÍMBOLOS MATEMÁTICOS? …”

“…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: “…-- 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: “…Potencia de base racional y exponente enteroRaíces; Propiedades de las Raíces; Practicando lo aprendido; Álgebra; Término algebraico y Expresión algebraica; Clasificación de expresiones algebraicas; Valoración de expresiones algebraicas; Operatoria de expresiones algebraicas; Términos Semejantes; Reducción de términos semejantes; Multiplicación de expresiones algebraicas; Productos Notables; Cuadrado de binomio; Cuadrado de un polinomio; Suma por su diferencia; Suma y Diferencia de cubo; Cubo de un binomio; Practicando lo aprendido…”

Tabla de Contenidos: “….); PÁGINA LEGAL; ÍNDICE; INTRODUCCIÓN; PRIMERA PARTE CIRCUITOS LÓGICOS DIGITALES; 1 COMPUERTAS LÓGICAS; Objetivo; Fundamento teórico; Material y equipo; Desarrollo; Sección de resultados; Resumen; 2 ÁLGEBRA DE BOOLE; Objetivo; Fundamento teórico; Desarrollo; Sección de resultados; Resumen; 3 USO DE TABLAS DE VERDAD (PARIDAD); Objetivo; Fundamento teórico; Material y equipo; Desarrollo; Sección de resultados; Resumen; 4 SUMA Y PRODUCTO CANÓNICOS; Objetivo; Fundamento teórico; Material y equipo; Desarrollo; Sección de resultados; Resumen…”

Tabla de Contenidos: “…Física I -- Página legal -- Índice -- Prólogo -- Presentación -- Introducción -- Estudiante lo que debes saber -- Modelaje de la herramienta cognitiva -- Perfil de competencias -- Generalidades -- Importancia de la física -- Introducción -- La prehistoria -- La importancia de las mediciones -- Sistema de mediciones -- Filósofos precursores de la física -- Física -- Modelo, teorías y leyes -- El método científico -- Clasificación de la física -- Análisis dimensional -- Magnitudes físicas -- Conceptos de masa, fuerza y peso -- Unidades de fuerza y peso -- Problemas propuestos -- Álgebra vectorial -- Estática -- Fuerzas de contacto y a distancia -- Sistema de fuerzas -- Método del polígono -- Descomposición de una fuerza según dos direcciones -- Métodos analíticos -- Método analítico del triángulo (para dos vectores) -- Método analítico del paralelogramo (...) -- Problemas resueltos -- Problemas propuestos -- Definición de producto vectorial de dos vectores -- Examen 1 -- Examen 2 -- Cinemática -- Definición -- Movimiento rectilíneo uniforme (mru) -- Leyes del mru -- Estructura meso reticular -- Problemas resueltos -- Problemas propuestos -- El movimiento variado o uniformemente variado -- Problema resueltos -- Problemas propuestos -- Caida libre -- Problemas resueltos -- Problemas propuestos -- Tiro vertical -- Problemas resueltos -- Problemas propuestos -- Tiro horizontal -- Problemas resueltos -- Problemas propuestos -- Tiro parabólico -- Problemas resueltos -- Problemas propuestos -- Examen 1 -- Examen 2 -- Movimiento circular uniforme -- Fuerza centrípeta -- Fuerza centrífuga -- Problemas resueltos -- Problemas propuestos -- Movimiento circular uniformemente variado mcuv -- Problemas resueltos -- Problemas propuestos -- Examen 1 -- Examen 2 -- Dinámica -- Estudiante, lo que debes saber -- Dinámica -- Unidades de fuerza y peso…”

Tabla de Contenidos: “…Funding Cannot Be Saved for Use in Later Implementation Periods Projects Begin Planning and Design in the First Year of an Implementation Period; Project Effects Are Offset by Planning, Design, and Construction Time; Projects Must Continually Operate; Handling and Processing of Data Within the Planning Tool; MySQL Database; Analytical Module; General Algebraic Modeling System Optimization Module; Tableau Results Visualizer; CHAPTER THREE: Analytic Procedures; Characterization of Projects; Project Costs and Duration of Implementation; Conflicts Among Projects…”

Tabla de Contenidos: “…A study of the complexity of respiratory signals during wake and sleepModel-based extraction of input and organ functions in dynamic medical imaging; A study on clustering for colour image quantisation; Sparse and robust signal reconstruction algorithm; An empirical study of algebraic-reconstruction techniques; Fast soft switching impulsive noise removal in color images; Analysis of the retinal nerve fiber layer texture related to the thickness measured by optical coherence tomography; A selective denoising method to remove speckle noise…”

Tabla de Contenidos: “…., c -- R Complements -- Dimensions -- Selections -- Projections -- Marginal distributions and scatter plot matrices -- Projection pursuit -- Projections for dimensions 1, 2, 3, ... 7 -- Parallel coordinates -- Sections, conditional distributions and coplots -- Transformations and dimension reduction -- Higher dimensions -- Linear case -- Partial residuals and added variable plots -- Non-linear case -- Example: cusp non-linearity -- Case study: Melbourne temperature data -- Curse of dimensionality -- Case study: body fat -- High dimensions -- Statistical summary -- R as a programming language and environment -- Help and information -- Names and search paths -- Administration and customisation -- Basic data types -- Output for objects -- Object inspection -- System inspection -- Complex data types -- Accessing components -- Data manipulation -- Operators -- Functions -- Debugging and profiling -- Control structures -- Input and output to data streams; external data -- Libraries, packages -- Mathematical operators and functions; linear algebra -- Model descriptions -- Graphic functions -- High-level graphics -- Low-level graphics -- Annotations and legends -- Graphic parameters and Llyout -- Elementary statistical functions -- Distributions, random numbers, densities... -- Computing on the language…”

Tabla de Contenidos: “…Lossy Compression -- Huffman Coding -- Storing the Huffman Tree -- Implementing a Compression Algorithm -- The Compression Stage -- The Decompression Stage -- Chapter Summary -- Chapter 7: Statistical Methods in Recommender Systems -- Recommender Systems -- The Functions of Recommender Systems -- Approaching the Problem -- First Approach -- Second Approach -- Final Approach -- Similarity Measures -- Cosine Similarity -- Euclidean Squared Distance -- Expected Ratings -- Laplace Smoothing -- Rating Probabilities -- Implementing the Algorithm -- The Main Program -- Chapter Summary -- Chapter 8: Reflections -- The Swift Programming Language -- Probability Theory -- Distributions -- Regression Techniques -- Hypothesis Testing -- Statistical Methods for Data Compression -- Statistical Methods in Recommender Systems -- Professional Areas of Application -- Data Scientist -- Machine Learning Engineer -- Data Engineer -- Data Analyst -- Topics for Further Studies -- Numerical Linear Algebra -- Multivariate Statistics -- Supervised Machine Learning -- Index…”

Tabla de Contenidos: “…CFD Techniques-The Basics -- 4.1 Introduction -- 4.2 Discretization of governing equations -- 4.3 Numerical solutions to algebraic equations -- 4.4 Summary -- Review questions -- Chapter 5. …”