Tabla de Contenidos: “…13.7 Change of Variables in multiple integrals -- Review Exercises -- 14 Vector calculus -- 14.1 Vector Fields -- 14.2 Line integrals -- 14.3 Conservative Vector Fields -- 14.4 Green's Theorem -- 14.5 Divergence and curl -- 14.6 Surface integrals -- 14.7 Stokes' Theorem -- 14.8 Divergence Theorem -- Review Exercises -- Appendix A Algebra review -- Appendix B Proofs of selected Theorems -- Answers -- Index -- Table of integrals…”

Tabla de Contenidos: “…2.9.1.3 Delete -- 2.9.1.4 Update -- 2.9.2 Network Model -- 2.9.2.1 Retrieval -- 2.9.2.2 Insert -- 2.9.2.3 Delete -- 2.9.2.4 Update -- 2.9.3 Relational Model -- 2.9.3.1 Retrieval -- 2.10 Database System Architecture -- Key Terms and Concepts -- Chapter Summary -- Practice Set -- Chapter 3: The Relational Model -- 3.1 Relational Databases Primer -- 3.1.1 Tabular Representation of Data -- 3.1.2 Some Terminology -- 3.1.3 Domains -- 3.2 Relational Database Characteristics -- 3.3 Relational Algebra -- 3.3.1 Relational Algebra Operators -- 3.3.1.1 Restrict -- 3.3.1.2 Project -- 3.3.1.3 Product -- 3.3.1.4 Union -- 3.3.1.5 Intersection -- 3.3.1.6 Difference -- 3.3.1.7 Join -- 3.3.1.8 Divide -- 3.3.2 Grouping -- 3.4 Relational Calculus -- 3.5 Database Integrity -- 3.5.1 Constraints -- 3.5.2 Declarative and Procedural Constraints -- 3.5.2.1 Type constraints -- 3.5.2.2 Attribute constraints -- 3.5.2.3 Instance constraints -- 3.5.2.4 Database constraints -- 3.5.3 More on Constraints -- 3.6 Keys -- 3.6.1 Superkey and Key -- 3.6.2 Composite Key -- 3.6.3 Candidate Key -- 3.6.4 Primary Key -- 3.6.5 Alternate Key or Secondary Key -- 3.6.6 Foreign Key -- 3.6.7 Keys and SQL -- 3.6.7.1 Defining primary keys in SQL -- 3.6.7.2 Defining foreign keys in SQL -- 3.7 Entity and Referential Integrity -- 3.7.1 Entity Integrity -- 3.7.2 Referential Integrity -- 3.8 Views -- 3.8.1 What is a View? …”

Tabla de Contenidos: “….); 5.4.1 PARÁMETROS ESTADÍSTICOS DE POSICIÓN; 5.4.2 MEDIDAS DE DISPERSIÓN; 5.5 EJERCICIOS; CAPÍTULO 6 INTRODUCCIÓN AL ÁLGEBRA MATRICIAL; 6.1 INTRODUCCIÓN A LAS MATRICES EN MATLAB; 6.1.1 GENERAR MATRICES. …”

Tabla de Contenidos: “…Intro -- Preface -- Setting up the Development Environment -- Simple Program -- Definitions: Packages, Imports, and Objects -- Object Definition -- The main Method -- Inside main -- Structure of a Scala Project -- Basic sbt Commands -- Activity: Performing Basic Operations with sbt: Build, Run, Package -- IDE -- Activity: Loading and Running a Sample Project in the IDE -- REPL -- Obtaining the Time Request from Our Chatbot Program -- Base Syntax -- Base Syntax for Definitions -- Base Syntax for Expressions -- Unit Testing -- Adding a Test to Our Project -- Inside Tests -- Running Tests for Chatbot -- Summary -- Basic Language Features -- Objects, Classes, and Traits -- Object -- Classes -- Equality and Case Classes -- Pattern Matching -- Traits -- Self-Types -- Special Classes -- OO in Our Chatbot -- Decoupling Logic and Environment -- Sealed Traits and Algebraic Datatypes -- Function Calls -- Syntax Goodies -- Named Parameters -- Default Parameters -- Currying Forms (Multiple Argument Lists) -- Special Magic Methods -- Implementing + in CartesianPoint -- Parameter-Passing Mode -- By Value -- By Name -- By Need -- Creating a Runnable Construction -- Printing the log Argument to the Console and File -- Summary -- Functions -- Functions -- Function Values -- Function from an OO Point of View -- Conversions -- Defining and Measuring the Time of a Unit Function -- Syntax Sugar in a Function Definition -- Partial Functions -- Exploring Pattern Matching -- Binding a Sequence of Variables in the Pattern Matcher -- Partial Functions in Practice -- Representing ChatbotMode as a Partial Function -- Implementing RemindStore as a Set of Partial Functions -- Using Lifting for Conversations between Total and Partial Functions -- Summary -- Scala Collections -- Working with Lists -- Constructing Lists -- Operations on Lists -- Pattern Matching on Lists…”

Tabla de Contenidos: “…Title Page; Copyright Page; About the Author; Contents; Preface; Chapter 1 A Signal Theoretic Introduction to Random Processes; 1.1 INTRODUCTION; 1.2 MOTIVATION; 1.2.1 Usefulness of Randomness; 1.2.2 Engineering; 1.3 BOOK OVERVIEW; Chapter 2 Background: Mathematics; 2.1 INTRODUCTION; 2.2 SET THEORY; 2.2.1 Basic Definitions; 2.2.2 Infinity; 2.2.3 Supremum and Infimum; 2.3 FUNCTION THEORY; 2.3.1 Function Definition; 2.3.2 Common Functions; 2.3.3 Function Properties; 2.4 MEASURE THEORY; 2.4.1 Sigma Algebra; 2.4.2 Measure; 2.4.3 Lebesgue Measure; 2.5 MEASURABLE FUNCTIONS…”

Tabla de Contenidos: “…A First Course in Applied Mathematics; CONTENTS; Preface; 1 Basics of Linear Algebra; 1.1 Notation and Terminology; 1.2 Vector and Matrix Norms; 1.3 Dot Product and Orthogonality; 1.4 Special Matrices; 1.4.1 Diagonal and triangular matrices; 1.4.2 Hessenberg matrices; 1.4.3 Nonsingular and inverse matrices; 1.4.4 Symmetric and positive definite matrices; 1.4.5 Matrix exponential; 1.4.6 Permutation matrices; 1.4.7 Orthogonal matrices; 1.5 Vector Spaces; 1.6 Linear Independence and Basis; 1.7 Orthogonalization and Direct Sums; 1.8 Column Space, Row Space, and Null Space…”

Tabla de Contenidos: “…3.4.2 Optical Communication Beaconing3.4.3 Network Architecture; 3.5 Evaluation; 3.5.1 Localization Accuracy; 3.5.2 Node Density; 3.5.3 Latency; 3.6 Conclusions; References; Chapter 4. Building an Algebraic Topological Model of Wireless Camera Networks; 4.1 Introduction; 4.2 Mathematical Background; 4.2.1 Simplicial Homology; 4.2.2 Example; 4.2.3 Cech Theorem; 4.3 The Camera and the Environment Models; 4.4 The CN-Complex; 4.5 Recovering Topology: 2D Case; 4.5.1 Algorithms; 4.5.2 Simulation in 2D; 4.6 Recovering Topology: 2.5D Case; 4.6.1 Mapping from 2.5D to 2D; 4.6.2 Building the CN-Complex…”

Tabla de Contenidos: “…2.5 SIGNED AND UNSIGNED NUMBERS2.6 BINARY ARITHMETIC; 2.7 ADDITION OF SIGNED NUMBERS; 2.8 BINARY-CODED DECIMAL REPRESENTATION; 2.9 BCD ADDITION; PROBLEMS; 3 Boolean Algebra and Logic; 3.1 OBJECTIVES; 3.2 BOOLEAN THEORY; 3.3 LOGIC VARIABLES AND LOGIC FUNCTIONS; 3.4 BOOLEAN AXIOMS AND THEOREMS; 3.5 BASIC LOGIC GATES AND TRUTH TABLES; 3.6 LOGIC REPRESENTATIONS AND CIRCUIT DESIGN; 3.7 TRUTH TABLE; 3.8 TIMING DIAGRAM; 3.9 LOGIC DESIGN CONCEPTS; 3.10 SUM-OF-PRODUCTS DESIGN; 3.11 PRODUCT-OF-SUMS DESIGN; 3.12 DESIGN EXAMPLES; 3.13 NAND AND NOR EQUIVALENT CIRCUIT DESIGN…”

Tabla de Contenidos: “…Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- Introduction -- Audience -- Course Adoption -- Errors -- Acknowledgments -- About the Authors -- Chapter 1: Data Collection and Cleaning -- Data-Collection Strategies -- Data Preprocessing Strategies -- Programming with R -- Data Types in R -- Data Structures in R -- Package Installation in R -- Reading and Writing Data in R -- Using the FOR Loop in R -- Using the WHILE Loop in R -- Using the IF-ELSE Statement in R -- Programming with Python -- Data Wrangling and Analytics in R and Python -- Structuring and Cleaning Data -- Missing Data -- Strategies for Dealing with Missing Data -- Data Deduplication -- Summary -- Exercise -- Notes -- References -- Chapter 2: Mathematical Background for Predictive Analytics -- Basics of Linear Algebra -- Vectors and Matrices -- Determinant -- Simple Linear Regression (SLR) -- Principal Component Analysis (PCA) -- Singular Value Decomposition (SVD) -- Introduction to Neural Networks -- Summary -- Exercise -- References -- Chapter 3: Introduction to Statistics, Probability, and Information Theory for Analytics -- Normal Distribution and the Central Limit Theorem -- Pearson Correlation Coefficient and Covariance -- Basic Probability for Predictive Analytics -- Conditional Probability -- Bayes' Theorem and Bayesian Classifiers -- Information Theory for Predictive Modeling -- Summary -- Exercise -- Notes -- References -- Chapter 4: Introduction to Machine Learning -- Statistical versus Machine Learning Models -- Regression Techniques -- Multiple Linear Regression (MLR) Model -- Assumptions of MLR -- Introduction to Multinomial Logistic Regression (MLogR) -- Bias versus Variance Trade-off -- Overfitting and Underfitting -- Regularization -- Ridge Regression -- Lasso Regression -- Summary -- Exercise…”

Tabla de Contenidos: “…-- Tools needed for flowcharts and pseudocode -- Pseudocode tools -- Flowchart tools -- Whiteboarding -- Design exercises -- The quadradic equation -- The beer program -- Final project - Robot startup system -- Design requirements -- Design logic -- Wait sequence -- Pseudocode -- Flowchart -- Summary -- Questions -- Chapter 6: Boolean Algebra -- Technical requirements -- What is Boolean algebra? …”

Tabla de Contenidos: “…9 TRANSISTORES -- 9.1 TIPOS DE TRANSISTORES -- 9.2 TRANSISTORES BIPOLARES -- 9.2.1 Polarización y funcionamiento -- 9.3 ENCAPSULADOS -- 9.4 IDENTIFICACIÓN DE TRANSISTORES -- 9.5 CURVAS CARACTERÍSTICAS -- 9.6 RECTA DE CARGA -- 9.7 PUNTO DE TRABAJO -- 10 AMPLIFICADORES OPERACIONALES -- 10.1 ESTRUCTURA INTERNA -- 10.2 ENCAPSULADOS -- 10.3 OPERACIÓN EN LAZO ABIERTO -- 10.4 OPERACIÓN EN LAZO CERRADO -- 10.5 PARÁMETROS REALES -- 11 ELECTRÓNICA DIGITAL -- 11.1 SISTEMA BINARIO -- 11.1.1 Conversión decimal-binario -- 11.1.2 Conversión binario-decimal -- 11.2 LÓGICA DIGITAL Y ÁLGEBRA BOOLEANA -- 11.3 FUNCIONES Y PUERTAS LÓGICAS -- 11.4 SIMPLIFICACIÓN DE FUNCIONES -- 11.5 EL TRANSISTOR COMO INTERRUPTOR -- 11.6 FAMILIAS DE CIRCUITOS INTEGRADOS DIGITALES -- 11.7 CIRCUITOS DE PULSOS -- 11.8 CIRCUITO INTEGRADO 555 -- 12 CIRCUITOS INTEGRADOS -- 12.1 HISTORIA DE LOS CI -- 12.2 TIPOS DE CIRCUITOS INTEGRADOS -- 12.3 ENCAPSULADOS E IDENTIFICACIÓN -- 12.4 CIRCUITOS INTEGRADOS LINEALES -- 12.4.1 Reguladores de voltaje -- 12.5 CIRCUITOS INTEGRADOS DIGITALES -- 12.5.1 Tipos de CI digitales -- 13 CIRCUITOS IMPRESOS -- 13.1 ¿QUÉ ES UN CIRCUITO IMPRESO? …”
Acceso restringido con credenciales UPSA

Tabla de Contenidos: “….) -- OPERACIONES CON MATRICES DISPERSAS -- OPERACIONES DE ÁLGEBRA LINEAL CON MATRICES DISPERSAS -- OPERACIONES CON MATRICES DISPERSAS -- PERMUTACIONES DE FILAS Y/O (...) -- CLASES Y OBJETOS -- PROGRAMACIÓN DE MATLAB -- BIFURCACIONES Y BUCLES -- SENTENCIA IF -- SENTENCIA SWITCH -- SENTENCIA FOR -- SENTENCIA WHILE -- SENTENCIA BREAK -- SENTENCIA CONTINUE -- SENTENCIAS TRY...CATCH...END -- LECTURA Y ESCRITURA INTERACTIVA DE VARIABLES -- FUNCIÓN INPUT -- FUNCIÓN DISP -- FICHEROS *.M -- FICHEROS DE COMANDOS (SCRIPTS) -- DEFINICIÓN DE FUNCIONES -- SENTENCIA RETURN -- FUNCIONES CON NÚMERO VARIABLE DE ARGUMENTOS -- HELP PARA LAS FUNCIONES DE USUARIO -- HELP DE DIRECTORIOS -- SUB-FUNCIONES -- FUNCIONES PRIVADAS -- FUNCIONES *.P -- VARIABLES PERSISTENTES -- VARIABLES GLOBALES -- REFERENCIAS DE FUNCIÓN (FUNCTION HANDLES) -- CREACIÓN DE REFERENCIAS DE FUNCIÓN -- EVALUACIÓN DE FUNCIONES MEDIANTE REFERENCIAS -- INFORMACIÓN CONTENIDA POR UNA (...) -- OTROS ASPECTOS DE LAS REFERENCIAS DE FUNCIÓN -- UTILIDAD DE LAS REFERENCIAS DE FUNCIÓN -- ENTRADA Y SALIDA DE DATOS -- IMPORTAR DATOS DE OTRAS APLICACIONES -- EXPORTAR DATOS A OTRAS APLICACIONES -- LECTURA Y ESCRITURA DE FICHEROS -- FUNCIONES FOPEN Y FCLOSE -- FUNCIONES FSCANF, SSCANF, FPRINTF Y SPRINTF -- FUNCIONES FREAD Y FWRITE -- FICHEROS DE ACCESO DIRECTO -- RECOMENDACIONES GENERALES DE PROGRAMACIÓN -- LLAMADA A COMANDOS DEL SISTEMA (...) -- FUNCIONES DE FUNCIÓN…”
Acceso restringido con credenciales UPSA

Tabla de Contenidos: “…14.7 Change of Variables in Multiple Integrals -- Review Exercises -- 15 Vector Calculus -- 15.1 Vector Fields -- 15.2 Line Integrals -- 15.3 Conservative Vector Fields -- 15.4 Green's Theorem -- 15.5 Divergence and Curl -- 15.6 Surface Integrals -- 15.7 Stokes' Theorem -- 15.8 Divergence Theorem -- Review Exercises -- A Appendix Algebra Review -- B Appendix Proofs of Selected Theorems -- Answers -- Index -- Table of Integrals…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credit -- Contributors -- Table of Contents -- Preface -- Part 1: Introduction to Neural Networks -- Chapter 1: Machine Learning - an Introduction -- Technical requirements -- Introduction to ML -- Different ML approaches -- Supervised learning -- Unsupervised learning -- Reinforcement learning -- Components of an ML solution -- Neural networks -- Introducing PyTorch -- Summary -- Chapter 2: Neural Networks -- Technical requirements -- The need for NNs -- The math of NNs -- Linear algebra -- An introduction to probability -- Differential calculus -- An introduction to NNs -- Units - the smallest NN building block -- Layers as operations -- Multi-layer NNs -- Activation functions -- The universal approximation theorem -- Training NNs -- GD -- Backpropagation -- A code example of an NN for the XOR function -- Summary -- Chapter 3: Deep Learning Fundamentals -- Technical requirements -- Introduction to DL -- Fundamental DL concepts -- Feature learning -- The reasons for DL's popularity -- Deep neural networks -- Training deep neural networks -- Improved activation functions -- DNN regularization -- Applications of DL -- Introducing popular DL libraries -- Classifying digits with Keras -- Classifying digits with PyTorch -- Summary -- Part 2: Deep Neural Networks for Computer Vision -- Chapter 4: Computer Vision with Convolutional Networks -- Technical requirements -- Intuition and justification for CNNs -- Convolutional layers -- A coding example of the convolution operation -- Cross-channel and depthwise convolutions -- Stride and padding in convolutional layers -- Pooling layers -- The structure of a convolutional network -- Classifying images with PyTorch and Keras -- Convolutional layers in deep learning libraries -- Data augmentation -- Classifying images with PyTorch -- Classifying images with Keras…”

Tabla de Contenidos: “…-- Data Science -- Data Science, Machine Learning, and Artificial Intelligence -- Common Applications of Data Science -- Data Science Best Practices -- Data Science Workflow Models -- Common Tools and Techniques -- Summary -- Exam Essentials -- Review Questions -- Chapter 2 Mathematics and Statistical Methods -- Calculus -- Derivatives -- Integrals -- Probability Distributions -- Continuous Probability Distributions -- Discrete Probability Distributions -- Inferential Statistics -- Estimating Population Parameters -- Hypothesis Testing -- Linear Algebra -- Vectors -- Matrices -- Summary -- Exam Essentials -- Review Questions -- Chapter 3 Data Collection and Storage -- Common Data Sources -- Generated Data -- Synthetic Data -- Commercial or Public Data -- Data Ingestion -- Data Ingestion Methods -- Infrastructure Requirements -- Data Ingestion Pipeline -- Data Storage -- Structured Storage -- Unstructured Storage -- Semi-Structured Storage -- Compressed Formats -- Managing the Data Lifecycle -- Data Lineage -- Refresh Cycles -- Archiving -- Summary -- Exam Essentials -- Review Questions -- Chapter 4 Data Exploration and Analysis -- Exploratory Data Analysis -- Quantitative Variables -- Qualitative Variables -- Univariate Analysis -- Bivariate Analysis -- Multivariate Analysis -- Choosing an Exploratory Data Analysis Method -- Common Data Quality Issues -- Structural Issues -- Temporal Issues -- Completeness Issues -- Summary -- Exam Essentials…”

Tabla de Contenidos: “…2.4.5 Printers -- 2.4.6 Telecommunications Equipment -- 2.4.7 Digital Cameras -- 2.4.8 Character Codes -- 2.5 SUMMARY -- 3 THE DIGITAL LOGIC LEVEL -- 3.1 GATES AND BOOLEAN ALGEBRA -- 3.1.1 Gates -- 3.1.2 Boolean Algebra -- 3.1.3 Implementation of Boolean Functions -- 3.1.4 Circuit Equivalence -- 3.2 BASIC DIGITAL LOGIC CIRCUITS -- 3.2.1 Integrated Circuits -- 3.2.2 Combinational Circuits -- 3.2.3 Arithmetic Circuits -- 3.2.4 Clocks -- 3.3 MEMORY -- 3.3.1 Latches -- 3.3.2 Flip-Flops -- 3.3.3 Registers -- 3.3.4 Memory Organization -- 3.3.5 Memory Chips -- 3.3.6 RAMs and ROMs -- 3.4 CPU CHIPS AND BUSES -- 3.4.1 CPU Chips -- 3.4.2 Computer Buses -- 3.4.3 Bus Width -- 3.4.4 Bus Clocking -- 3.4.5 Bus Arbitration -- 3.4.6 Bus Operations -- 3.5 EXAMPLE CPU CHIPS -- 3.5.1 The Intel Core i7 -- 3.5.2 The Texas Instruments OMAP4430 System-on-a-Chip -- 3.5.3 The Atmel ATmega168 Microcontroller -- 3.6 EXAMPLE BUSES -- 3.6.1 The PCI Bus -- 3.6.2 PCI Express -- 3.6.3 The Universal Serial Bus -- 3.7 INTERFACING -- 3.7.1 I/O Interfaces -- 3.7.2 Address Decoding -- 3.8 SUMMARY -- 4 THE MICROARCHITECTURE LEVEL -- 4.1 AN EXAMPLE MICROARCHITECTURE -- 4.1.1 The Data Path -- 4.1.2 Microinstructions -- 4.1.3 Microinstruction Control: The Mic-1 -- 4.2 AN EXAMPLE ISA: IJVM -- 4.2.1 Stacks -- 4.2.2 The IJVM Memory Model -- 4.2.3 The IJVM Instruction Set -- 4.2.4 Compiling Java to IJVM -- 4.3 AN EXAMPLE IMPLEMENTATION -- 4.3.1 Microinstructions and Notation -- 4.3.2 Implementation of IJVM Using the Mic-1 -- 4.4 DESIGN OF THE MICROARCHITECTURE LEVEL -- 4.4.1 Speed versus Cost -- 4.4.2 Reducing the Execution Path Length -- 4.4.3 A Design with Prefetching: The Mic-2 -- 4.4.4 A Pipelined Design: The Mic-3 -- 4.4.5 A Seven-Stage Pipeline: The Mic-4 -- 4.5 IMPROVING PERFORMANCE -- 4.5.1 Cache Memory -- 4.5.2 Branch Prediction -- 4.5.3 Out-of-Order Execution and Register Renaming…”

Tabla de Contenidos: “…QUÍMICA TEÓRICA Y COMPUTACIONAL ; PÁGINA LEGAL; ÍNDICE; CAPÍTULO 1 FUNDAMENTOS; 1.1 ÁLGEBRA LINEAL; 1.1.1 Matrices; 1.1.1.1 Definiciones sobre matrices.; 1.1.1.2 Propiedades de las matrices.; 1.1.2 Determinantes; 1.1.3 Espacios vectoriales complejos n-dimensionales; 1.1.3.1 Notación de Dirac.; 1.1.3.2 Vectores.; 1.1.3.3 Operadores en el espacio real de tres dimensiones.; 1.1.4 Cambio de base; 1.1.5 Valores propios; 1.1.5.1 Ecuación de valores propios.; 1.1.5.2 Propiedades de los vectores y valores propios de una matriz Hermítica.; 1.1.5.3 Ortogonalización de vectores…”

Tabla de Contenidos: “…Vector quantization by transform2.5.6. Algebraic vector quantization; 2.6. Gain-shape vector quantization; 2.6.1. …”

Tabla de Contenidos: “…Introduction; 1.1 About This Book; 1.2 Graphics on Handheld Devices; 1.3 Mobile Graphics Standards; Part I: Anatomy of a Graphics Engine; Chapter 2. Linear Algebra for 3D Graphics; 2.1 Coordinate Systems; 2.2 Matrices; 2.3 Affine Transformations; 2.4 Eye Coordinate System; 2.5 Projections; 2.6 Viewport and 2D Coordinate Systems; Chapter 3. …”

Tabla de Contenidos: “…Introduction; 1.1 Pictures; 1.1.1 Pixels, voxels, and their values; 1.1.2 Picture resolution and picture size; 1.1.3 Scan orders; 1.1.4 Adjacency and connectedness; 1.2 Digital Geometry and Related Disciplines; 1.2.1 Coordinates and metric spaces; 1.2.2 Euclidean, similarity, and affine geometry; 1.2.3 Projective geometry; 1.2.4 Vector and geometric algebra; 1.2.5 Graph theory; 1.2.6 Topology; 1.2.7 Approximation and estimation; 1.2.8 Combinatorial geometry; 1.2.9 Computational geometry; 1.2.10 Fuzzy geometry…”