Tabla de Contenidos: “…-- Setting up our environment -- Data representation -- Creating tensors -- Tensor rank -- Properties of tensors -- Basic tensor operations -- Hello World in TensorFlow -- Debugging and solving error messages -- Summary -- Questions -- Further reading -- Chapter 3: Linear Regression with TensorFlow -- Technical requirements -- Linear regression with TensorFlow -- Evaluating regression models -- Salary prediction with TensorFlow -- Loading the data -- Data preprocessing -- Model building -- Model evaluation -- Making predictions -- Saving and loading models -- Summary -- Questions -- Further reading -- Chapter 4: Classification with TensorFlow -- Technical requirements -- Classification with TensorFlow -- Evaluating classification models -- Confusion matrix -- A student dropout prediction -- Loading the data -- Exploratory data analysis -- Data preprocessing -- Model building -- Classification performance evaluation -- Summary -- Questions…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright Page -- Dedication -- Preface -- Table of Contents -- 1: Variational Analysis and Variational Rationality in Behavioral Sciences: Stationary Traps -- 1.1 Introduction -- 1.2 Variational Rationality in Behavioral Sciences -- 1.2.1 Desirability and Feasibility Aspects of Human Behavior -- 1.2.2 Worthwhile (Desirable and Feasible) Moves -- 1.3 Evaluation Aspects of Variational Rationality -- 1.3.1 Optimistic and Pessimistic Evaluations -- 1.3.2 Optimistic Evaluations of Reference-Dependent Payoffs -- 1.4 Exact Stationary Traps in Behavioral Dynamics -- 1.5 Evaluations of Approximate Stationary Traps -- 1.6 Geometric Evaluations and Extremal Principle -- 1.7 Summary of Major Finding and Future Research -- References -- 2: A Financial Model for a Multi-Period Portfolio Optimization Problem with a Variational Formulation -- 2.1 Introduction -- 2.2 The Financial Model -- 2.3 Variational Inequality Formulation and Existence Results -- 2.4 Numerical Examples -- 2.5 Conclusions -- References -- 3: How Variational Rational Agents Would Play Nash: A Generalized Proximal Alternating Linearized Method -- 3.1 Introduction -- 3.2 Potential Games: How to Play Nash? …”

Tabla de Contenidos: “…. -- Chapter 6: Building a Classification Model with Spark * -- Types of classification models -- Linear models -- Logistic regression -- Multinomial logistic regression -- Visualizing the StumbleUpon dataset -- Extracting features from the Kaggle/StumbleUpon evergreen classification dataset -- StumbleUponExecutor -- Linear support vector machines -- The naà ̄ve Bayes model -- Decision trees -- Ensembles of trees -- Random Forests -- Gradient-Boosted trees -- Multilayer perceptron classifier -- Extracting the right features from your data -- Training classification models…”

Tabla de Contenidos: “…Chapter 13 Quiz -- Answers to Chapter 13 Quiz -- Book 5: Solving Linear and Polynomial Equations -- Chapter 14: Establishing Ground Rules for Solving Equations -- Creating the Correct Setup for Solving Equations…”

Tabla de Contenidos: “…. -- Further reading -- Chapter 9: Finding Optimal Solutions -- Technical requirements -- Minimizing a simple linear function -- Getting ready -- How to do it... -- How it works... -- There's more... -- Minimizing a non-linear function -- Getting ready -- How to do it... -- How it works... -- There's more... -- Using gradient descent methods in optimization -- Getting ready -- How to do it... -- How it works... -- There's more... -- Using least squares to fit a curve to data -- Getting ready -- How to do it... -- How it works... -- There's more... -- Analyzing simple two-player games -- Getting ready -- How to do it... -- How it works... -- There's more... -- Computing Nash equilibria -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Further reading -- Chapter 10: Improving Your Productivity -- Technical requirements -- Keeping track of units with Pint -- Getting ready -- How to do it... -- How it works... -- There's more... -- Accounting for uncertainty in calculations -- Getting ready -- How to do it... -- How it works... -- There's more... -- Loading and storing data from NetCDF files -- Getting ready -- How to do it... -- How it works... -- There's more... -- Working with geographical data -- Getting ready -- How to do it... -- How it works... -- Executing a Jupyter notebook as a script -- Getting ready -- How to do it... -- How it works…”

Tabla de Contenidos: “…Rename -- 13.11 Environment Variables -- 13.12 I/O Re direction -- Summary -- Exercises -- Chapter 14: Linear Data Structure -- 14.1 Introduction to Data Structure -- 14.2 List -- 14.3 Implementation of a List -- 14.4 Traversal of a List -- 14.5 Searching and Retrieving an Element -- 14.6 Predecessor and Successor -- 14.7 Insertion -- 14.8 Deletion -- 14.9 Sorting -- 14.10 Merging Lists -- 14.11 Representation of a Stack -- 14.12 Stack-Related Terms…”

Tabla de Contenidos: “…3.6.1 Image Formats, Containers, and Compression Standards -- 3.7 Speech and Audio Coding -- 3.8 Shannon-Fano Coding -- 3.9 Human Coding -- 3.10 Arithmetic Coding -- 3.11 Lempel-Ziv-Welch Coding -- 3.12 Run-length Encoding -- 3.13 MPEG Audio and Video Coding Standards -- 3.14 Psychoacoustic Model of Human Hearing -- 3.14.1 The Masking Phenomenon -- 3.14.2 Temporal Masking -- 3.14.3 Perceptual Coding in MPEG Audio -- 3.15 Dolby -- 3.16 Linear Predictive Coding Model -- 3.17 Solved Problems -- Multiple Choice Questions -- Review Questions -- Part B: Error Control Coding -- Chapter 4: Coding Theory -- 4.1 Introduction -- 4.2 Types of Codes -- 4.2.1 Code Rate -- 4.3 Types of Errors -- 4.4 Error Control Strategies -- 4.4.1 Throughput Efficiency of ARQ -- 4.5 Mathematical Fundamentals -- 4.5.1 Modular Arithmetic -- 4.5.2 Sets -- 4.5.3 Groups -- 4.5.4 Fields -- 4.5.5 Arithmetic of Binary Field -- 4.5.6 Roots of Equations -- 4.5.7 Galois Field -- 4.6 Vector Spaces -- 4.6.1 Subspace -- 4.6.2 Linear Combination -- 4.6.3 Basis (or Base) -- 4.6.4 Dimension -- 4.6.5 Orthogonality -- 4.6.6 Dual Space -- 4.7 Matrices -- 4.7.1 Row Space -- 4.8 Solved Problems -- Multiple Choice Questions -- Review Questions -- Chapter 5: Linear Block Codes -- 5.1 Introduction -- 5.2 Generator Matrices -- 5.3 Parity-Check Matrices -- 5.3.1 Dual Code -- 5.4 Error Syndrome -- 5.4.1 Undetectable Error Pattern -- 5.5 Error Detection -- 5.6 Minimum Distance -- 5.7 Error-detecting Capability -- 5.8 Error-correcting Capability -- 5.9 Standard Array and Syndrome Decoding -- 5.9.1 Coset and Coset Leader -- 5.10 Probability of Undetected Errors Over a BSC -- 5.11 Hamming Code -- 5.12 Solved Problems -- Multiple Choice Questions -- Review Questions -- Chapter 6: Cyclic Codes -- 6.1 Introduction -- 6.2 Generation -- 6.2.1 Generation and Parity-check Matrices -- 6.2.2 Realization of Cyclic Code…”

Tabla de Contenidos: “…Programming by visualizing the big picture -- Summary -- Chapter 3: Predicting Votes with Linear Models -- Required packages -- Setting up the data -- Training and testing datasets -- Predicting votes with linear models -- Checking model assumptions -- Checking linearity with scatter plots -- Checking normality with histograms and quantile-quantile plots -- Checking homoscedasticity with residual plots -- Checking no collinearity with correlations -- Measuring accuracy with score functions -- Programatically finding the best model -- Generating model combinations -- Predicting votes from wards with unknown data -- Summary -- Chapter 4: Simulating Sales Data and Working with Databases -- Required packages -- Designing our data tables -- The basic variables -- Simplifying assumptions -- Potential pitfalls -- The too-much-empty-space problem -- The too-much-repeated-data problem -- Simulating the sales data -- Simulating numeric data according to distribution assumptions -- Simulating categorical values using factors -- Simulating dates within a range -- Simulating numbers under shared restrictions -- Simulating strings for complex identifiers -- Putting everything together -- Simulating the client data -- Simulating the client messages data -- Working with relational databases -- Summary -- Chapter 5: Communicating Sales with Visualizations -- Required packages -- Extending our data with profit metrics -- Building blocks for reusable high-quality graphs -- Starting with simple applications for bar graphs -- Adding a third dimension with colors -- Graphing top performers with bar graphs -- Graphing disaggregated data with boxplots -- Scatter plots with joint and marginal distributions -- Pricing and profitability by protein source and continent -- Client birth dates, gender, and ratings -- Developing our own graph type - radar graphs…”

Tabla de Contenidos: “…-- Deep learning frameworks -- Setting up a cloud-based deep learning environment with GPU support -- Choosing a cloud provider -- Setting up your virtual server -- Configuring your virtual server -- Installing and updating deep learning dependencies -- Accessing your deep learning cloud environment -- Validating GPU-enablement on your deep learning environment -- Setting up a robust, on-premise deep learning environment with GPU support -- Neural network basics -- A simple linear neuron…”

Tabla de Contenidos: “…Subpart G-Sources for Brachytherapy -- Subpart H-Sealed Sources for Diagnosis -- Subpart I-Teletherapy -- Subpart J-Training and Experience Requirements -- Subpart K-Enforcement -- PART 36-LICENSES AND RADIATION SAFETY REQUIREMENTS FOR IRRADIATORS -- Subpart A-General Provisions -- Subpart B-Specific Licensing Requirements -- Subpart C-Design and Performance Requirements for Irradiators -- Subpart D-Operation of Irradiators -- Subpart E-Records -- Subpart F-Enforcement -- E Nuclear Regulatory Commission Agreement and Non-agreement States -- AGREEMENT STATES -- NON-AGREEMENT STATES -- F Regulatory Chronology -- G History of Radiation Regulation in Medicine -- PROFESSIONAL SELF-REGULATION -- GOVERNMENT REGULATION -- NUCLEAR REGULATORY COMMISSION -- Atomic Energy Act -- Other Federal Agencies -- Federal Radiation Council -- Other Executive Agencies -- PHS Radiological Health Program -- Environmental Protection Agency -- STATE REGULATION -- REFERENCES -- H Public Meeting Documents -- ORGANIZATIONS FORMALLY CONTACTED FOR PUBLIC MEETING PARTICIPATION -- COMMITTEE FOR REVIEW AND EVALUATION OF THE MEDICAL USE PROGRAM OF THE NUCLEAR REGULATORY COMMISSION -- PUBLIC MEETING ANNOUNCEMENT AND REQUEST FOR WRITTEN TESTIMONY -- Background -- Providing Testimony -- Guide to Preparing Testimony -- TOPICS -- Regulation -- Data/Risk -- Quality Management/Quality Assurance -- Education -- Other -- PUBLIC HEARING OCTOBER 12, 1994 ORGANIZATIONS AND INDIVIDUALS SUBMITTING TESTIMONY -- QUESTION SUMMARIES -- I Quality Management Technical Panel -- LIST OF PARTICIPANTS, TUESDAY, OCTOBER 11, 1994 -- Speakers -- Observers -- Subcommitee Members -- J Commissioned Papers -- K The Linear, No-Threshold Model -- ADOPTION OF THE LINEAR, NO-THRESHOLD MODEL -- Divided Scientific Opinion, 1958-1966 -- Joint Committee on Atomic Energy Hearings, 1957-1960s…”

Tabla de Contenidos: “…Manuel Sanchis Guarner, Josep Giner, Germà Colón / volum preparat per Antoni Ferrando -- 5. …”

Tabla de Contenidos: “…Manuel Sanchis Guarner, Josep Giner, Germà Colón / volum preparat per Antoni Ferrando -- 5. …”

Tabla de Contenidos: “…P 500 Returns -- 6.4.1.2 Linear Regression for Predicting S&amp -- P 500 Returns -- 6.4.2 Prediction of 10‐Year Bond Returns -- 6.4.2.1 10‐Year Bond Returns -- 6.4.2.2 Linear Regression for Predicting 10‐Year Bond Returns -- Part II Risk Management -- Chapter 7 Volatility Prediction -- 7.1 Applications of Volatility Prediction -- 7.1.1 Variance and Volatility Trading -- 7.1.2 Covariance Trading -- 7.1.3 Quantile Estimation -- 7.1.4 Portfolio Selection -- 7.1.5 Option Pricing -- 7.2 Performance Measures for Volatility Predictors -- 7.3 Conditional Heteroskedasticity Models -- 7.3.1 GARCH Predictor -- 7.3.1.1 Predicting the Squared Returns -- 7.3.1.2 Predicting the Realized Volatility -- 7.3.1.3 S&amp -- P 500 Volatility Prediction with GARCH(1,1) -- 7.3.2 ARCH Predictor -- 7.3.2.1 Predicting the Squared Returns -- 7.3.2.2 S&amp -- P 500 Volatility Prediction with ARCH(p) -- 7.4 Moving Average Methods -- 7.4.1 Sequential Sample Variance -- 7.4.2 Exponentially Weighted Moving Average -- 7.4.2.1 Asymmetric Exponentially Weighted Moving Average -- 7.5 State Space Predictors -- 7.5.1 Linear Regression Predictor -- 7.5.1.1 Prediction with Volatility and Mean -- 7.5.1.2 Prediction with Past Squared Returns -- 7.5.2 Kernel Regression Predictor -- Chapter 8 Quantiles and Value‐at‐Risk -- 8.1 Definitions of Quantiles -- 8.2 Applications of Quantiles -- 8.2.1 Reserve Capital -- 8.2.1.1 Value‐at‐Risk of a Portfolio -- 8.2.1.2 Decomposition of the Loss of a Portfolio -- 8.2.1.3 Losses over Several Periods -- 8.2.2 Margin Requirements -- 8.2.3 Quantiles as a Risk Measure -- 8.3 Performance Measures for Quantile Estimators -- 8.3.1 Measuring the Probability of Exceedances -- 8.3.1.1 Cross‐Validation -- 8.3.1.2 Probability Differences -- 8.3.1.3 Confidence of the Performance Measure -- 8.3.1.4 Probability Differences Over All Time Intervals…”

“…¿Cuáles son los recursos de poder que un primer mandatario puede generar durante el ejercicio del poder para lograr la estabilidad política? …”
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“…Escribir guiones supone generar tramas arriesgadas y a la vez verosímiles para los personajes que inventamos. …”
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Tabla de Contenidos: “…ALGUNOS INDICIOS PARA GENERAR LOS CONCEPTOS -- 2. PERSPECTIVA DE MAPEO -- CONCLUSIÓN -- CAPÍTULO V: LA ESCRITURA DE TEXTOS CIENTÍFICOS -- INTRODUCCIÓN -- EL PROCESO DE CONSTRUCCIÓN DEL TEXTO -- 1. …”

“…Si este libro consigue generar esperanza en aquellas personas que sufren dolor, habremos conseguido nuestro objetivo…”

“…Al finalizar el curso, el alumno podrá crear un nuevo proyecto, realizar un presupuesto con sus mediciones, generar informes y exportar e importar proyectos. …”