Tabla de Contenidos: “…Cover -- About the Author -- Contents -- Preface -- Chapter 1: Matrices and Linear Systems of Equations -- 1.1 Introduction -- 1.1.1 Matrix: Definition -- 1.1.2 Types of Matrices -- 1.2 Algebra of Matrices -- 1.3 Matrix Multiplication -- 1.3.1 Properties -- 1.4 Determinant of a Square Matrix -- 1.4.1 Expansion of a Determinant of Third Order -- 1.4.2 Expansion of the Determinant of a Matrix of any Order n -- 1.4.3 Properties of Determinant of a Matrix A -- 1.5 Related Matrices -- 1.5.1 The Transpose of a Matrix: Properties -- 1.5.2 Adjoint of a Square Matrix -- 1.5.3 Invertible Matrix -- 1.5.4 Submatrix of a Matrix -- 1.6 Determinant-related Matrices -- 1.6.1 Singular Matrix -- 1.6.2 Nonsingular Matrix -- 1.6.3 Properties of Invertible Matrices (Non Singular Matrices) -- 1.7 Special Matrices -- 1.7.1 Idempotent Matrix -- 1.7.2 Nilpotent Matrix -- 1.7.3 Involutory Matrix -- 1.7.4 Periodic Matrix -- Exercise 1.1 -- 1.8 Linear Systems of Equations -- 1.8.1 Introduction -- 1.9 Homogeneous (H) and Nonhomogeneous (NH) Systems of Equations -- 1.9.1 Matrix Form of the Linear System -- 1.10 Elementary Row and Column Operations (Transformations) for Matrices -- 1.10.1 Equivalence of Matrices -- 1.10.2 Vectors: Linear Dependence and Independence -- 1.10.3 Rank of a Matrix: Definition 1 -- 1.10.4 Methods for Determining Linear Dependence (L.D.) and Linear Independence (L.I.) of Vectors -- Exercise 1.2 -- 1.11 Inversion of a Nonsingular Matrix -- 1.11.1 Method 1: Adjoint Method (or Determinants Method) -- 1.11.2 Elementary Matrices -- 1.11.3 Method 2: Gauss-Jordan6-7 Method of Finding the Inverse of a Matrix -- Exercise 1.3 -- 1.12 Rank of a Matrix -- 1.12.1 Rank of a Matrix: Definition 2 -- 1.13 Methods for Finding the Rank of a Matrix -- 1.13.1 Method 1: Maximum Number of Linearly Independent Rows -- 1.13.2 Method 2: Method of Minors (Enumeration Method)…”

Tabla de Contenidos: “…Facturación en Software de Brasil, año 2000; Cuadro 7. Ranking de las mayores empresas de Tecnología de Información Brasileras 2001…”

“…In the late 1950s, Suzuki Seijun was an unknown, anxious low-ranking film director churning out so-called program pictures for Japan's most successful movie studio, Nikkatsu. …”

Tabla de Contenidos: “…-- The prediction problem -- The ranking problem -- Types of recommender systems -- Collaborative filtering -- User-based filtering -- Item-based filtering -- Shortcomings -- Content-based systems -- Knowledge-based recommenders -- Hybrid recommenders -- Summary -- Chapter 2: Manipulating Data with the Pandas Library -- Technical requirements -- Setting up the environment -- The Pandas library -- The Pandas DataFrame -- The Pandas Series -- Summary -- Chapter 3: Building an IMDB Top 250 Clone with Pandas -- Technical requirements -- The simple recommender -- The metric -- The prerequisties -- Calculating the score -- Sorting and output -- The knowledge-based recommender -- Genres -- The build_chart function -- Summary -- Chapter 4: Building Content-Based Recommenders -- Technical requirements -- Exporting the clean DataFrame -- Document vectors -- CountVectorizer -- TF-IDFVectorizer -- The cosine similarity score -- Plot description-based recommender -- Preparing the data -- Creating the TF-IDF matrix -- Computing the cosine similarity score -- Building the recommender function -- Metadata-based recommender -- Preparing the data -- The keywords and credits datasets -- Wrangling keywords, cast, and crew -- Creating the metadata soup -- Generating the recommendations -- Suggestions for improvements -- Summary -- Chapter 5: Getting Started with Data Mining Techniques -- Problem statement -- Similarity measures -- Euclidean distance -- Pearson correlation -- Cosine similarity -- Clustering -- k-means clustering -- Choosing k -- Other clustering algorithms -- Dimensionality reduction -- Principal component analysis…”

Tabla de Contenidos: “…Marco Porzionato, Federica De Marco -- 20. “New” Rankings on the Scene: The U21 Ranking of National Higher Education Systems and U-Multirank. …”

Tabla de Contenidos: “…Change detection based on structured covariances -- 3.5.1. Low-rank Gaussian change detector -- 3.5.2. Low-rank compound Gaussian change detector -- 3.5.3. …”

Tabla de Contenidos: “…Inbound Marketing -- 3. EdgeRank -- 4. Marketing para fans -- 5. Optimizar la interacción -- 6. …”

Tabla de Contenidos: “…Intro -- Title Page -- Copyright -- Credits -- Table of Contents -- Preface -- Lesson 1: From Data to Decisions - Getting Started with TensorFlow -- Taking Decisions Based on Data - Titanic Example -- Data Value Chain for Making Decisions -- From Disaster to Decision - Titanic Survival Example -- General Overview of TensorFlow -- Installing and Configuring TensorFlow -- Installing TensorFlow on Linux -- Installing Python and nVidia Driver -- Installing NVIDIA CUDA -- Installing NVIDIA cuDNN v5.1+ -- Installing the libcupti-dev Library -- Installing TensorFlow -- Installing TensorFlow from Source -- Testing Your TensorFlow Installation -- TensorFlow Computational Graph -- TensorFlow Programming Model -- Data Model in TensorFlow -- Tensors -- Rank -- Shape -- Data Type -- Variables -- Fetches -- Feeds and Placeholders -- TensorBoard -- How Does TensorBoard Work? …”

Tabla de Contenidos: “…; 18 How Do I Really Call Someone Out on Their Mess When They Have More Rank Than I Do?; 19 As a Department Head or Supervisor, How Do I Really Get People Past Conflicts in the Workplace Once They Have Escalated Badly?…”

Tabla de Contenidos: “…""REFERENCES""""PRODUCTIVITY""; ""INTRODUCTION""; ""SUGGESTED OUTLINE FOR PLANNING STUDIES OF PRODUCTIVITY OR QUALITY""; ""MEASURES OF PRODUCTIVITY""; ""Publication Counts""; ""CITATIONS""; ""JOURNALS AND SUBFIELDS""; ""PEER ASSESSMENT""; ""GRANTS AND GRANT APPLICATIONS""; ""ACADEMIC RANK, RATE OF ADVANCEMENT, SALARY""; ""HONORS AND AWARDS""; ""MENTORING""; ""PATENTS""; ""SUMMARY""; ""REFERENCES""; ""APPENDIX: SCIENCE STUDIES RESOURCES""; ""HEALTH SERVICES RESEARCH PERSONNEL: DEMAND, SUPPLY, AND ADEQUACY OF TRAINING RESOURCES""; ""INTRODUCTION""; ""WHO CONDUCTS HEALTH SERVICES RESEARCH?""…”

Tabla de Contenidos: “…A Flexible Class of Reduced Rank Spatial Models for Large Non-Gaussian Dataset…”

Tabla de Contenidos: “…Grupos estratégicos, capital reputacional y rankings. 5. Conclusiones y principales implicaciones del estudio de los grupos estratégicos en el sistema universitario español. 5.1. …”

Tabla de Contenidos: “…Chapter 7: Querying Our Data, Part 2 - Postprocessing and Response Synthesis -- Technical requirements -- Re-ranking, transforming, and filtering nodes using postprocessors -- Exploring how postprocessors filter, transform, and re-rank nodes -- SimilarityPostprocessor -- KeywordNodePostprocessor -- PrevNextNodePostprocessor -- LongContextReorder -- PIINodePostprocessor and NERPIINodePostprocessor -- MetadataReplacementPostprocessor -- SentenceEmbeddingOptimizer -- Time-based postprocessors -- Re-ranking postprocessors -- Final thoughts about node postprocessors -- Understanding response synthesizers -- Implementing output parsing techniques -- Extracting structured outputs using output parsers -- Extracting structured outputs using Pydantic programs -- Building and using query engines -- Exploring different methods of building query engines -- Advanced uses of the QueryEngine interface -- Hands-on - building quizzes in PITS -- Summary -- Chapter 8: Building Chatbots and Agents with LlamaIndex -- Technical requirements -- Understanding chatbots and agents -- Discovering ChatEngine -- Understanding the different chat modes -- Implementing agentic strategies in our apps -- Building tools and ToolSpec classes for our agents -- Understanding reasoning loops -- OpenAIAgent -- ReActAgent -- How do we interact with agents? …”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright Page -- About the Author -- About the Technical Editor -- Acknowledgments -- Contents at a Glance -- Contents -- Introduction -- Who I Am and Why I'm Writing About This Topic -- Who This Book Is For -- Why You Should Learn SQL if You Want to Be a Data Scientist -- What I Hope You Gain from This Book -- Conventions -- Reader Support for This Book -- Companion Download Files -- How to Contact the Publisher -- How to Contact the Author -- Chapter 1 Data Sources -- Data Sources -- Tools for Connecting to Data Sources and Editing SQL -- Relational Databases -- Dimensional Data Warehouses -- Asking Questions About the Data Source -- Introduction to the Farmer's Market Database -- A Note on Machine Learning Dataset Terminology -- Exercises -- Chapter 2 The SELECT Statement -- The SELECT Statement -- The Fundamental Syntax Structure of a SELECT Query -- Selecting Columns and Limiting the Number of Rows Returned -- The ORDER BY Clause: Sorting Results -- Introduction to Simple Inline Calculations -- More Inline Calculation Examples: Rounding -- More Inline Calculation Examples: Concatenating Strings -- Evaluating Query Output -- SELECT Statement Summary -- Exercises Using the Included Database -- Chapter 3 The WHERE Clause -- The WHERE Clause -- Filtering SELECT Statement Results -- Filtering on Multiple Conditions -- Multi-Column Conditional Filtering -- More Ways to Filter -- BETWEEN -- IN -- LIKE -- IS NULL -- A Warning About Null Comparisons -- Filtering Using Subqueries -- Exercises Using the Included Database -- Chapter 4 CASE Statements -- CASE Statement Syntax -- Creating Binary Flags Using CASE -- Grouping or Binning Continuous Values Using CASE -- Categorical Encoding Using CASE -- CASE Statement Summary -- Exercises Using the Included Database -- Chapter 5 SQL JOINs -- Database Relationships and SQL JOINs -- A Common Pitfall when Filtering Joined Data -- JOINs with More than Two Tables -- Exercises Using the Included Database -- Chapter 6 Aggregating Results for Analysis -- GROUP BY Syntax -- Displaying Group Summaries -- Performing Calculations Inside Aggregate Functions -- MIN and MAX -- COUNT and COUNT DISTINCT -- Average -- Filtering with HAVING -- CASE Statements Inside Aggregate Functions -- Exercises Using the Included Database -- Chapter 7 Window Functions and Subqueries -- ROW NUMBER -- RANK and DENSE RANK -- NTILE -- Aggregate Window Functions -- LAG and LEAD -- Exercises Using the Included Database -- Chapter 8 Date and Time Functions -- Setting datetime Field Values -- EXTRACT and DATE_PART -- DATE_ADD and DATE_SUB -- DATEDIFF -- TIMESTAMPDIFF -- Date Functions in Aggregate Summaries and Window Functions -- Exercises -- Chapter 9 Exploratory Data Analysis with SQL -- Demonstrating Exploratory Data Analysis with SQL -- Exploring the Products Table -- Exploring Possible Column Values -- Exploring Changes Over Time -- Exploring Multiple Tables Simultaneously -- Exploring Inventory vs. …”

Tabla de Contenidos: “…3.8.1 Computing the Eigenvector Centrality -- 3.9 PageRank Centrality -- 3.9.1 Computing the PageRank Centrality -- 3.10 Hub and Authority -- 3.10.1 Computing the Hub and Authority Centralities -- 3.11 Network Centralities Calculation by Group -- 3.11.1 By Group Network Centralities -- 3.12 Summary -- Chapter 4 Network Optimization -- 4.1 Introduction -- 4.1.1 History -- 4.1.2 Network Optimization in SAS Viya -- 4.2 Clique -- 4.2.1 Finding Cliques -- 4.3 Cycle -- 4.3.1 Finding Cycles -- 4.4 Linear Assignment -- 4.4.1 Finding the Minimum Weight Matching in a Worker-Task Problem -- 4.5 Minimum-Cost Network Flow -- 4.5.1 Finding the Minimum-Cost Network Flow in a Demand-Supply Problem -- 4.6 Maximum Network Flow Problem -- 4.6.1 Finding the Maximum Network Flow in a Distribution Problem -- 4.7 Minimum Cut -- 4.7.1 Finding the Minimum Cuts -- 4.8 Minimum Spanning Tree -- 4.8.1 Finding the Minimum Spanning Tree -- 4.9 Path -- 4.9.1 Finding Paths -- 4.10 Shortest Path -- 4.10.1 Finding Shortest Paths -- 4.11 Transitive Closure -- 4.11.1 Finding the Transitive Closure -- 4.12 Traveling Salesman Problem -- 4.12.1 Finding the Optimal Tour -- 4.13 Vehicle Routing Problem -- 4.13.1 Finding the Optimal Vehicle Routes for a Delivery Problem -- 4.14 Topological Sort -- 4.14.1 Finding the Topological Sort in a Directed Graph -- 4.15 Summary -- Chapter 5 Real-World Applications in Network Science -- 5.1 Introduction -- 5.2 An Optimal Tour Considering a Multimodal Transportation System - The Traveling Salesman Problem Example in Paris -- 5.3 An Optimal Beer Kegs Distribution - The Vehicle Routing Problem Example in Asheville -- 5.4 Network Analysis and Supervised Machine Learning Models to Predict COVID-19 Outbreaks -- 5.5 Urban Mobility in Metropolitan Cities…”

Tabla de Contenidos: “…Chapter 6: Making Interactive Reports -- Introduction -- Creating R Markdown reports -- Learning the markdown syntax -- Embedding R code chunks -- Creating interactive graphics with ggvis -- Understanding basic syntax and grammar -- Controlling axes and legends -- Using scales -- Adding interactivity to a ggvis plot -- Creating an R Shiny document -- Publishing an R Shiny report -- Chapter 7: Simulation from Probability Distributions -- Introduction -- Generating random samples -- Understanding uniform distributions -- Generating binomial random variates -- Generating Poisson random variates -- Sampling from a normal distribution -- Sampling from a chi-squared distribution -- Understanding Student's t-distribution -- Sampling from a dataset -- Simulating the stochastic process -- Chapter 8: Statistical Inference in R -- Introduction -- Getting confidence intervals -- Performing Z-tests -- Performing student's T-tests -- Conducting exact binomial tests -- Performing Kolmogorov-Smirnov tests -- Working with the Pearson's Chi-squared tests -- Understanding the Wilcoxon Rank Sum and Signed Rank tests -- Conducting one-way ANOVA -- Performing two-way ANOVA -- Chapter 9: Rule and Pattern Mining with R -- Introduction -- Transforming data into transactions -- Displaying transactions and associations -- Mining associations with the Apriori rule -- Pruning redundant rules -- Visualizing association rules -- Mining frequent itemsets with Eclat -- Creating transactions with temporal information -- Mining frequent sequential patterns with cSPADE -- Chapter 10: Time Series Mining with R -- Introduction -- Creating time series data -- Plotting a time series object -- Decomposing time series -- Smoothing time series -- Forecasting time series -- Selecting an ARIMA model -- Creating an ARIMA model -- Forecasting with an ARIMA model…”

Tabla de Contenidos: “…Contradictions -- Equivalence -- Exclusive Or and Exclusive Nor -- Logical Proofs -- Deductive Inferences -- Fuzzy Logic -- Approximate Reasoning -- Other Forms of the Implication Operation -- Part II: Fuzzy Systems -- Natural Language -- Linguistic Hedges -- Fuzzy (Rule-Based) Systems -- Aggregation of Fuzzy Rules -- Graphical Techniques of Inference -- Summary -- References -- Problems -- Chapter 6 Historical Methods of Developing Membership Functions -- Membership Value Assignments -- Intuition -- Inference -- Rank Ordering -- Neural Networks -- Genetic Algorithms -- Inductive Reasoning -- Summary -- References -- Problems -- Chapter 7 Automated Methods for Fuzzy Systems -- Definitions -- Batch Least Squares Algorithm -- Recursive Least Squares Algorithm -- Gradient Method -- Clustering Method -- Learning from Examples -- Modified Learning from Examples -- Summary -- References -- Problems -- Chapter 8 Fuzzy Systems Simulation -- Fuzzy Relational Equations -- Nonlinear Simulation Using Fuzzy Systems -- Fuzzy Associative Memories (FAMs) -- Summary -- References -- Problems -- Chapter 9 Decision Making with Fuzzy Information -- Fuzzy Synthetic Evaluation -- Fuzzy Ordering -- Nontransitive Ranking -- Preference and Consensus -- Multiobjective Decision Making -- Fuzzy Bayesian Decision Method -- Decision Making under Fuzzy States and Fuzzy Actions -- Example Summary -- Summary -- References -- Problems -- Chapter 10 Fuzzy Classification and Pattern Recognition -- Fuzzy Classification -- Classification by Equivalence Relations -- Crisp Relations -- Fuzzy Relations -- Cluster Analysis -- Cluster Validity -- c-Means Clustering -- Hard c-Means (HCM) -- Fuzzy c-Means (FCM) -- Fuzzy c-Means Algorithm -- Classification Metric -- Hardening the Fuzzy c-Partition -- Similarity Relations from Clustering -- Fuzzy Pattern Recognition…”

Tabla de Contenidos: “…Historia y filosofía de la historia después de Hegel -- Más allá del sistema -- Un caso de polisemia conceptual: el "historicismo" -- Leopold von Ranke -- El positivismo -- Historismo e historicismo: Karl R. …”
Acceso restringido con credenciales, usuarios UPSA

Tabla de Contenidos: “…Historia y filosofía de la historia después de Hegel -- Más allá del sistema -- Un caso de polisemia conceptual: el "historicismo" -- Leopold von Ranke -- El positivismo -- Historismo e historicismo: Karl R. …”
Acceso restringido con credenciales, usuarios UPSA

Tabla de Contenidos: “…; A Coach's/Trainer's Guide to Helping Leaders Improve Emotional Intelligence; How to Use This Guide and How Not to Use It; A Guide to the 50 Emotional Intelligence Activities; Suggested Training Formats; EQ 1 Champion or Chump; EQ 2 Importance Meter; EQ 3 Adding Fuel to the Importance Meter; EQ 4 Rank Order Your Employees; EQ 5 Ask for Feedback; EQ 6 Picture Yourself; EQ 7 Personality Contest; EQ 8 Music of Our Workplace; EQ 9 Coming Through; EQ 10 Open and Friendly Versus Friendship; EQ 11 Listening Habits; EQ 12 Genuine Listening…”