Tabla de Contenidos: “…Technical requirements -- Understanding features and descriptors -- FAST corner detection -- Corner detection using the imcorner function -- Comparing performance -- BRIEF - efficient duplicate detection method -- Identifying image duplicates -- Creating a panorama from many images -- ORB, rotation invariant image matching -- BRISK - scale invariant image matching -- FREAK - fastest scale and rotation invariant matching -- Running face recognition -- Summary -- Questions -- Chapter 6: Introduction to Neural Networks -- Technical requirements -- Introduction -- The need for neural networks -- The need for MXNet -- First steps with the MNIST dataset -- Getting the data -- Preparing the data -- Defining a neural network -- Fitting the network -- Improving the network -- Predicting new images -- Putting it all together -- Multiclass classification with the CIFAR-10 dataset -- Getting and previewing the dataset -- Preparing the data -- Starting with the linear classifier -- Reusing the MNIST architecture -- Improving the network -- Accuracy - why at almost 70 -- Putting it all together -- Classifying cats versus dogs -- Getting and previewing the dataset -- Creating an image data iterator -- Training the model -- Putting it all together -- Reusing your models -- Saving the model -- Loading the model -- Summary -- Questions -- Further reading -- Chapter 7: Using Pre-Trained Neural Networks -- Technical requirements -- Introduction to pre-trained networks -- Transfer learning -- MXNet Model Zoo -- Predicting image classes using Inception V3 -- Setting up the Inception V3 environment -- Loading the network -- Preparing the datasets -- Running predictions -- Expected performance -- Putting it all together -- Predicting an image class using MobileNet V2 -- Setting up the environment -- Loading the network -- Preparing the datasets -- Running the predictions…”

Tabla de Contenidos: “…Cover; Title Page; Copyright; Contents; Preface; Part I Linear Models: Regression and ANOVA; Chapter 1 The Linear Model; 1.1 Regression, Correlation, and Causality; 1.2 Ordinary and Generalized Least Squares; 1.2.1 Ordinary Least Squares Estimation; 1.2.2 Further Aspects of Regression and OLS; 1.2.3 Generalized Least Squares; 1.3 The Geometric Approach to Least Squares; 1.3.1 Projection; 1.3.2 Implementation; 1.4 Linear Parameter Restrictions; 1.4.1 Formulation and Estimation; 1.4.2 Estimability and Identifiability; 1.4.3 Moments and the Restricted GLS Estimator; 1.4.4 Testing With h=0 1.4.5 Testing With Nonzero h1.4.6 Examples; 1.4.7 Confidence Intervals; 1.5 Alternative Residual Calculation; 1.6 Further Topics; 1.7 Problems; 1.A Appendix: Derivation of the BLUS Residual Vector; 1.B Appendix: The Recursive Residuals; 1.C Appendix: Solutions; Chapter 2 Fixed Effects ANOVA Models; 2.1 Introduction: Fixed, Random, and Mixed Effects Models; 2.2 Two Sample t-Tests for Differences in Means; 2.3 The Two Sample t-Test with Ignored Block Effects; 2.4 One-Way ANOVA with Fixed Effects; 2.4.1 The Model; 2.4.2 Estimation and Testing; 2.4.3 Determination of Sample Size 2.4.4 The ANOVA Table2.4.5 Computing Confidence Intervals; 2.4.6 A Word on Model Assumptions; 2.5 Two-Way Balanced Fixed Effects ANOVA; 2.5.1 The Model and Use of the Interaction Terms; 2.5.2 Sums of Squares Decomposition Without Interaction; 2.5.3 Sums of Squares Decomposition With Interaction; 2.5.4 Example and Codes; Chapter 3 Introduction to Random and Mixed Effects Models; 3.1 One-Factor Balanced Random Effects Model; 3.1.1 Model and Maximum Likelihood Estimation; 3.1.2 Distribution Theory and ANOVA Table; 3.1.3 Point Estimation, Interval Estimation, and Significance Testing 3.1.4 Satterthwaite's Method3.1.5 Use of SAS; 3.1.6 Approximate Inference in the Unbalanced Case; 3.1.6.1 Point Estimation in the Unbalanced Case; 3.1.6.2 Interval Estimation in the Unbalanced Case; 3.2 Crossed Random Effects Models; 3.2.1 Two Factors; 3.3 Nested Random Effects Models; 3.3.1 Two Factors; 3.3.1.3 Mixed Model Case; 3.3.2 Three Factors; 3.3.2.1 All Effects Random; 3.3.2.2 Mixed: Classes Fixed; 3.3.2.3 Mixed: Classes and Subclasses Fixed; 3.4 Problems; 3.A Appendix: Solutions; Part II Time Series Analysis: ARMAX Processes; Chapter 4 The AR(1) Model; 4.1 Moments and Stationarity 4.2 Order of Integration and Long-Run Variance4.3 Least Squares and ML Estimation; 4.3.1 OLS Estimator of a; 4.3.2 Likelihood Derivation I; 4.3.3 Likelihood Derivation II; 4.3.4 Likelihood Derivation III; 4.3.5 Asymptotic Distribution; 4.4 Forecasting; 4.5 Small Sample Distribution of the OLS and ML Point Estimators; 4.6 Alternative Point Estimators of a; 4.6.1 Use of the Jackknife for Bias Reduction; 4.6.2 Use of the Bootstrap for Bias Reduction; 4.6.3 Median-Unbiased Estimator; 4.6.4 Mean-Bias Adjusted Estimator; 4.6.5 Mode-Adjusted Estimator; 4.6.6 Comparison --…”

Tabla de Contenidos:

Tabla de Contenidos: “…Build Typesafe Generic Classes; 2.5.2. What about...; 2.6. Make Simple Data Types Nullable; 2.6.2. …”

Tabla de Contenidos: “…Summarizing Aggregated Classes; 2.10.2. Solution; 2.10.3. Discussion; 2.11. …”

Tabla de Contenidos: “…Global namespace; 1.10. Classes; 1.10.2. Fields; 1.10.2.2. The readonly modifier; 1.10.3. …”

Tabla de Contenidos: “…Identifiers; 2.6. Complex Classes; 2.6.2. Composition; 2.7. Behavior; 2.7.2. …”

Tabla de Contenidos: “…Calling Lua functions from C -- Calling C functions from Lua -- Working with tables in C -- Reading values from a table -- Writing values to a table -- Meta tables -- User data -- Lua C API reference -- Summary -- Chapter 7: Lua Bridge -- Technical requirements -- API conventions -- Namespaces -- Variables -- Functions -- Properties -- Classes -- Constructor -- Subclass -- Member variables, properties, and functions -- Static variables, properties, and functions -- Calling C functions from Lua -- LuaRef -- LuaRef and tables -- Summary -- Chapter 8: Next Steps -- Books -- Programming In Lua -- Learning Game AI Programming with Lua -- LÖVE for Lua Game Programming -- Lua Game Development Cookbook -- Game Development with Lua -- Beginning Lua Programming -- Lua Programming Gems -- Learn Lua for iOS Game Development -- Game engines -- LÖVE 2D -- Defold -- Corona -- Leadwerks -- Gideros -- Urho 3D -- Polycode -- ShiVa -- Game mods -- Roblox -- Garry's Mod -- World Of Warcraft -- Natural Selection 2 -- Don't Starve -- Hack 'n' Slash -- Scriptable software -- CEGUI -- Conky -- Premake -- Moho -- Summary -- Other Books You May Enjoy -- Index…”

Tabla de Contenidos: “…A Java Performance Toolbox -- Operating System Tools and Analysis -- CPU Usage -- The CPU Run Queue -- Disk Usage -- Network Usage -- Java Monitoring Tools -- Basic VM Information -- Thread Information -- Class Information -- Live GC Analysis -- Heap Dump Postprocessing -- Profiling Tools -- Sampling Profilers -- Instrumented Profilers -- Blocking Methods and Thread Timelines -- Native Profilers -- Java Mission Control -- Java Flight Recorder -- Enabling JFR -- Selecting JFR Events -- Summary -- Chapter 4. …”

Tabla de Contenidos: “…Illustrations On Special Cases -- 2.4 Exercises -- Bibliography -- 3 The RUL Loss Rate for a Special Class of Time-To-Failure Distributions*: MRL Linear Function of Time -- 3.1 Characterizing the Special Family of Distributions -- 3.2 Limiting Cases -- 3.2.1 Exponential Distribution -- 3.2.2 Dirac Distribution -- 3.2.3 Uniform Distribution -- 3.3 Synopsis -- 3.4 RUL Distribution, Coefficient of Variation of TTF and RUL -- 3.4.1 Coefficient of Variation of the Time to Failure -- 3.4.2 Coefficient of Variation of the RUL -- 3.5 Confidence Interval for RUL and Relation to RUL Loss Rate -- 3.6 Higher-Order Moments and Moment-Generating Function -- 3.6.1 Moment-Generating Function -- 3.6.2 Moment-Generating Function for Special TTF Family -- 3.7 Cumulative Hazard Function -- 3.8 Exercises -- Bibliography -- 4 Generalization to an MRL Piecewise-Linear Function of Time -- 4.1 Reliability Function, MRL, and Failure Rate -- 4.2 Exercises -- Bibliography -- 5 Generalization to a Wide Class of Lifetime Distributions -- 5.1 Introduction: Generalization Method -- 5.2 Nonlinear Time Transformation -- 5.3 Confidence Interval for RUL -- 5.4 Application to Weibull Distribution -- 5.4.1 Derivation of the Nonlinear Transformation -- 5.4.2 Derivation of Confidence Intervals for the RUL -- 5.5 Application to Gamma Distribution -- 5.6 Application to the Lognormal Distribution…”

Tabla de Contenidos: “…Cover -- Copyright -- Contributors -- Table of Contents -- Preface -- Chapter 1: Acquiring Financial Data -- Getting data from Yahoo Finance -- Getting data from Nasdaq Data Link -- Getting data from Intrinio -- Getting data from Alpha Vantage -- Getting data from CoinGecko -- Summary -- Chapter 2: Data Preprocessing -- Converting prices to returns -- Adjusting the returns for inflation -- Changing the frequency of time series data -- Different ways of imputing missing data -- Converting currencies -- Different ways of aggregating trade data -- Summary -- Chapter 3: Visualizing Financial Time Series -- Basic visualization of time series data -- Visualizing seasonal patterns -- Creating interactive visualizations -- Creating a candlestick chart -- Summary -- Chapter 4: Exploring Financial Time Series Data -- Outlier detection using rolling statistics -- Outlier detection with the Hampel filter -- Detecting changepoints in time series -- Detecting trends in time series -- Detecting patterns in a time series using the Hurst exponent -- Investigating stylized facts of asset returns -- Summary -- Chapter 5: Technical Analysis and Building Interactive Dashboards -- Calculating the most popular technical indicators -- Downloading the technical indicators -- Recognizing candlestick patterns -- Building an interactive web app for technical analysis using Streamlit -- Deploying the technical analysis app -- Summary -- Chapter 6: Time Series Analysis and Forecasting -- Time series decomposition -- Testing for stationarity in time series -- Correcting for stationarity in time series -- Modeling time series with exponential smoothing methods -- Modeling time series with ARIMA class models -- Finding the best-fitting ARIMA model with auto-ARIMA -- Summary -- Chapter 7: Machine Learning-Based Approaches to Time Series Forecasting…”

Tabla de Contenidos: “…El seguiment i la metodologia de les classes per a adults; 4.4.8. Xocs culturals; 5. Conclusions; 6. …”

Tabla de Contenidos: “…Sexual Options for People with Disabilities: Using Personal Assistance Services for Sexual ExpressionWORST CASE SCENARIOS: INTERSECTIONS OF GENDER, DISABILITY, ETHNICITY, CLASS AND SOCIAL DISAPPROVAL; Substance Abuse, Disabilities, and Black Women: An Issue Worth Exploring; Women with Physical Disabilities Who Want to Leave Their Partners: A Feminist and Disability-Affirmative Perspective; Prostitution and the Invisibility of Harm; EMPOWERMENT: USING CULTURE AND CONTEXT TO ENHANCE AND FACILITATE FEMINIST THERAPY; INTEGRATING SPIRITUALITY, HISTORY, AND WOMEN'S WAYS OF KNOWING INTO THERAPY…”

Tabla de Contenidos: “…The roman army and the emergence of a ‘business class’in the northwestern provinces of the roman empire (1st century BCE–3rd century CE) / ‘Militia in Urbe’. …”

Tabla de Contenidos: “…Considerations in Facilitating Antimicrobial StewardshipConclusion; Bibliography; Section II Classes of Antimicrobial Agents; 8 Beta-lactam Antibiotics: Penam Penicillins; Introduction to Beta-lactam Antibiotics; Bibliography; Penam Penicillins; Group 1 Benzyl Penicillin and Long-Acting Parenteral Forms; Bibliography; Group 2 Orally Absorbed Penicillins; Group 3 Antistaphylococcal Isoxazolyl Penicillins: Cloxacillin, Dicloxacillin, Methicillin, Nafcillin, and Oxacillin; Bibliography; Bibliography; Group 4 Extended-Spectrum Penicillins: Amidopenicillins: Mecillinam…”

Tabla de Contenidos: “…-- Recurrent neural networks for time series forecasting -- Convolutional neural networks -- 2D convolutions -- 1D convolution -- 1D convolution for time series forecasting -- Summary -- Appendix: Getting Started with Python -- Installation -- Python installers -- Running the examples -- Basic data types -- List, tuple, and set -- Strings -- Maps -- Keywords and functions -- Iterators, iterables, and generators -- Iterators -- Iterables -- Generators -- Classes and objects -- Summary -- Index…”

Tabla de Contenidos: “…3 Early Life Transitions Increase the Risk for HIV Infection: Using Latent Class Growth Models to Assess the Effect of Key Life Events on HIV Incidence Among Adolescent Girls in Rural South Africa -- Introduction -- Methods -- Study design -- Statistical analysis -- Missing data -- Measures -- Results -- Specific life events and HIV incidence -- Cumulative life events and HIV incidence -- Conclusions -- References -- 4 Achieving the Sustainable Development Goals: Evidence from the Longitudinal Parenting Across Cultures Project -- Introduction -- Participants -- Procedure and measures…”

Tabla de Contenidos: “…Definitions and Notes by Country; III. Definitions of Classes of Non-life Insurance; I. Définitions et notes communes; II. …”

Tabla de Contenidos: “…Chapter 6: Internal Collaboration: Marrying Off-Centeredness to a World-Class OrganizationInterview; Cindy Dunson, Director of Human Resources at Dogfish Head; Off-Centeredness Is about Our Culture; Experimental Brewing; Interview; Mariah Calagione, Vice President, Dogfish Head; "This Is the Road We're All Going Down Together"; Chapter 7: External Collaboration; External and Internal Collaboration; Giving Back; Our Community; Interview; Nick Brayton, President, Woolrich; Treating the Brand the Right Way; Chapter 8: Collaborative Creativity: Passion and Patience; Interview…”

Tabla de Contenidos: “…""Using the Spring Framework""""Spring Framework and Dependency Injection""; ""Summary""; ""Chapter 3: Applying Different Configurations""; ""My Documents XML Configuration""; ""Using Spring Annotations""; ""Spring Stereotypes""; ""Using the Java Bean Configuration""; ""Using the GroovyBeanDefinitionReader Class""; ""Which Configuration to Choose?""; ""Summary""; ""Chapter 4: Using Beans Scopes""; ""Scopes""; ""Using the @Scope Annotation""; ""Using Bean Scopes in the New GroovyBeanDefinitionReader Context""; ""Summary""; ""Chapter 5: Working with Collections and Custom Types""…”