“…Y hubo un cuentista, fotógrafo, escritor de panfletos y libros de adivinanzas, llamado Lewis Carroll, que revolucionó el estudio de la lógica, el álgebra y la geometría, y cuyos logros marcan un antes y un después en estas disciplinas…”

Tabla de Contenidos: “…Autómatas programables; Página legal; Índice general; Presentación; Introducción; Introducción; Conceptos básicos; Automatismos; El autómata programable industrial; Factores cuantitativos; Factores cualitativos; Principio de funcionamiento de autómata; Nociones sobre sistemas lógicos; Sistemas de numeración; Sistema binario; Sistema hexadecimal; Códigos de numeración; Códigos binarios; Código decimal codificado en binario - BCD; Códigos alfanuméricos; Concepto de Registro; Álgebra de Boole; Leyes de álgebra de Boole; Funciones lógicas; Sistemas combinacionales; Sistemas secuenciales…”

Tabla de Contenidos: “….; 2.5 Ejercicios del Capítulo; 3 Producto Directo y Convolución de Funciones Generalizadas; 3.1 Producto Directo; 3.2 Convolución de funciones generalizadas; 3.3 Propiedades de la convolución; 3.4 Algebra convolucional D+ de funciones generalizadas; 3.5 Ecuaciones en el álgebra convolucional (...); 3.6 Regularización de las funciones generalizadas; 3.7 Ejemplos de convoluciones; 3.8 Ejercicios del Capítulo; 4 Funciones generalizadas de crecimiento lento…”

Tabla de Contenidos: “…Chapter 4: Simple SQL RetrievalChoosing Columns; Ordering the Result Table; Choosing Rows; Nulls and Retrieval: Three-Valued Logic; Chapter 5: Retrieving Data from More Than One Table: Joins; The Relational Algebra Join Operation; SQL Syntax for Inner Joins; Finding Multiple Rows in One Table: Joining a Table to Itself; Outer Joins; Valid versus Invalid Joins; Avoiding Joins with Uncorrelated Subqueries; Chapter 6: Advanced Retrieval Operations; Union; Negative Queries; The EXISTS Operator; CASE Expressions; Chapter 7: Calculations and Grouping Queries; Performing Arithmetic…”

Tabla de Contenidos: “…Creating a multidimensional arraySelecting NumPy array elements; NumPy numerical types; Data type objects; Character codes; The dtype constructors; The dtype attributes; One-dimensional slicing and indexing; Manipulating array shapes; Stacking arrays; Splitting NumPy arrays; NumPy array attributes; Converting arrays; Creating array views and copies; Fancy indexing; Indexing with a list of locations; Indexing NumPy arrays with Booleans; Broadcasting NumPy arrays; Summary; Chapter 3: Statistics and Linear Algebra; NumPy and SciPy modules; Basic descriptive statistics with NumPy…”

Tabla de Contenidos: “…Intro -- Contents -- Part I: All About the ASVAB -- Chapter 1 Deciding on Military Service -- Army -- Navy -- Air Force -- Marine Corps -- Coast Guard -- Making the Choice -- Chapter 2 Introducing the ASVAB -- ASVAB Test Areas -- Taking the Test -- Chapter 3 ASVAB Scores and Score Reports -- Norm-Referenced Testing and Standard Scores -- Scores -- Receiving Your Score -- Retaking the Test -- Chapter 4 The ASVAB and Military Entrance AFQT Scores and Eligibility for Enlistment -- AFQT Score -- Educational Requirements for Enlistment -- Eligibility for Enlistment -- Job Eligibility -- Chapter 5 Taking the CAT-ASVAB -- What to Expect on the CAT-ASVAB -- Comparing the CAT-ASVAB to the ASVAB -- Chapter 6 Steps to Acing the ASVAB -- Preparing for the Test -- Test Day -- Taking the Test -- A Final Word -- Part II: ASVAB Practice Diagnostic Tests -- Chapter 7 Practice Diagnostic Tests -- Practice Diagnostic Test Answers -- Part III: Review of All ASVAB Test Topics -- Chapter 8 General Science -- Physics -- Chemistry -- Human Physiology -- The Senses -- Biology -- Ecology -- Earth and Space Science -- Geology -- The Atmosphere -- Reading and Reviewing -- Chapter 9 Arithmetic Reasoning 1: The Basics -- Operations -- Exponents -- Order of Operations -- Prime and Composite Numbers -- Fractions -- Chapter 10 Arithmetic Reasoning 2: Word Problems -- Basic Word Problems -- Percents -- Rates and Ratios -- Area and Perimeter -- Chapter 11 Word Knowledge -- Word Origins and Derivations -- Root Words -- Prefixes and Suffixes -- Context Clues -- Synonyms and Antonyms -- Technical Language -- Reading -- Chapter 12 Paragraph Comprehension -- Finding Specific Information -- Main Ideas -- Author's Viewpoint -- Context Clues -- Inference -- Reading and Comprehending -- Chapter 13 Mathematics Knowledge 1:Algebra and Probability -- Algebra -- Probability…”

Tabla de Contenidos: “…OscillationsDamped oscillations; Combining sine waves; Vectors and basic vector algebra; What are vectors?; Vectors vs. scalars; Adding and subtracting vectors; Resolving vectors: vector components; Position vectors; Adding vectors using components; Multiplying a vector by a number; Vector magnitude; Vector angle; Multiplying vectors: Scalar or dot product; Multiplying vectors: Vector or cross product; Building a Vector object with vector algebra; Simple calculus ideas; Slope of a line: gradient; Rates of change: derivatives; Discrete calculus: difference equations; Doing sums: integrals…”

Tabla de Contenidos: “…Game Theory -- A Game for Linear-time - Branching-time Spectroscopy -- On Satisficing in Quantitative Games -- Quasipolynomial Computation of Nested Fixpoints -- SMT Verification -- A Flexible Proof Format for SAT Solver-Elaborator Communication -- Generating Extended Resolution Proofs with a BDD-Based SAT Solver -- Bounded Model Checking for Hyperproperties -- Counterexample-Guided Prophecy for Model Checking Modulo the Theory of Arrays -- SAT Solving with GPU Accelerated Inprocessing -- FOREST: An Interactive Multi-tree Synthesizer for Regular Expressions -- Probabilities -- Finding Provably Optimal Markov Chains -- Inductive Synthesis for Probabilistic Programs Reaches New Horizons -- Analysis of Markov Jump Processes under Terminal Constraints -- Multi-objective Optimization of Long-run Average and Total Rewards -- Inferring Expected Runtimes of Probabilistic Integer Programs Using Expected Sizes -- Probabilistic and Systematic Coverage of Consecutive Test-Method Pairs for Detecting Order-Dependent Flaky Tests -- Timed Systems -- Timed Automata Relaxation for Reachability -- Iterative Bounded Synthesis for Efficient Cycle Detection in Parametric Timed Automata -- Algebraic Quantitative Semantics for Efficient Online Temporal Monitoring -- Neural Networks -- Synthesizing Context-free Grammars from Recurrent Neural Networks -- Automated and Formal Synthesis of Neural Barrier Certificates for Dynamical Models -- Improving Neural Network Verification through Spurious Region Guided Refinement -- Analysis of Network Communication Resilient Capacity-Aware Routing -- Network Traffic Classification by Program Synthesis. …”

Tabla de Contenidos: “…Imperative Programming; Designing Types; What About Nulls?; Algebraic Data Types and Abstract Data Types; Exercises; Chapter 3. …”

“…Sin embargo, han realizado grandes aportaciones al álgebra, a la geometría o al cálculo, por citar algunas disciplinas. …”
Acceso restringido con credenciales UPSA. Para su lectura requiere realizar el préstamo.
Tutorial de uso Xebook

“…Actualment és catedràtic d'Àlgebra de la Universitat de València…”
Texto completo en Odilo

“…Part 1, The Emergence of Sets within Mathematics, surveys the initial motivations for a mathematical notion of a set within several branches of the discipline (geometry, algebra, algebraic number theory, real and complex analysis), emphasizing the role played by Riemann in fostering acceptance of the set-theoretic approach. …”

“…Intended as an intermediate microeconomics text,Perloff introduces economic theory through a combination of calculus, algebra,and graphs. It then integrates estimated, real-life problems and applications,using a step-by-step approach to demonstrate how microeconomic theory can beapplied to solve practical problems and policy issues. …”

“…Course prerequisites include basic knowledge of linear algebra, probability, statistics, and familiarity with R. …”

“…What You Will Learn Manipulate the key attributes and universal functions of NumPy Utilize matrix and mathematical computation using linear algebra modules Implement regression and curve fitting for models Perform time frequency / spectral density analysis using the Fourier Transform modules Collate with the distutils and setuptools modules used by other Python libraries Establish Cython with NumPy arrays Write extension modules for NumPy code using the C API Build sophisticated data structures using NumPy array with libraries such as Panda and Scikits In Detail In today's world of science and technology, it's all about speed and flexibility. …”

“…Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. …”

“…Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more. …”

“…What You Will Learn Learn concepts of data modelling and relation algebra Install and set up PostgreSQL database server and client software Implement data structures in PostgreSQL Manipulate data in the database using SQL Implement data processing logic in the database with stored functions, triggers and views Test database solutions and assess the performance Integrate database with Java applications Detailed knowledge of the main PostgreSQL building objects, most used extensions Practice database development life cycle including analysis, modelling, (documentation), testing, bug fixes and refactoring In Detail PostgreSQL is one of the most powerful and easy to use database management systems. …”

“…Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. …”

“…If you’re familiar with high school Algebra 2 and basic statistics, you’re good to go. …”