“…Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R 4, Second Edition details how data science is a combination of statistics, computational science, and machine learning. …”

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“…Beginning entity framework core five…”

Tabla de Contenidos: “…Beginning ActionScript 2.0; About the Authors; Acknowledgments; Contents; Introduction; Who This Book Is For; How This Book Is Structured; What You Need to Use This Book; Conventions; Source Code; Errata; Chapter 1: Getting Started with Macromedia Flash; Introducing the Development Environment; About the Library and Symbols; Setting Up Your Scripting Environment; Summary; Exercises; Chapter 2: Getting Started with ActionScript 2.0; Understanding Statements; Understanding Operators; Using White Space; Using Comments; Introducing Variables; Working with Collections of Data; Summary; Exercises…”

Tabla de Contenidos: “…Beginning SQL Server 2005 Administration; About the Authors; Credits; Acknowledgments; Contents; Introduction; Who This Book Is For; What This Book Covers; How This Book Is Structured; What You Need to Use This Book; Conventions; Source Code; Errata; p2p.wrox.com; Chapter 1: Introducing SQL Server 2005; What Is SQL Server 2005?…”

Tabla de Contenidos: “…8.8 Summary -- Chapter 9: Overfitting -- 9.1 Model Capacity -- 9.2 Overfitting and Underfitting -- 9.2.1 Underfitting -- 9.2.2 Overfitting -- 9.3 Dataset Division -- 9.3.1 Validation Set and Hyperparameters -- 9.3.2 Early Stopping -- 9.4 Model Design -- 9.5 Regularization -- 9.5.1 L0 Regularization -- 9.5.2 L1 Regularization -- 9.5.3 L2 Regularization -- 9.5.4 Regularization Effect -- 9.6 Dropout -- 9.7 Data Augmentation -- 9.7.1 Rotation -- 9.7.2 Flip -- 9.7.3 Cropping -- 9.7.4 Generate Data -- 9.7.5 Other Methods -- 9.8 Hands-On Overfitting -- 9.8.1 Build the Dataset -- 9.8.2 Influence of the Number of Network Layers -- 9.8.3 Impact of Dropout -- 9.8.4 Impact of Regularization -- 9.9 References -- Chapter 10: Convolutional Neural Networks -- 10.1 Problems with Fully Connected N -- 10.1.1 Local Correlation -- 10.1.2 Weight Sharing -- 10.1.3 Convolution Operation -- 10.2 Convolutional Neural Network -- 10.2.1 Single-Channel Input and Single Convolution Kernel -- 10.2.2 Multi-channel Input and Single Convolution Kernel -- 10.2.3 Multi-channel Input and Multi-convolution Kernel -- 10.2.4 Stride Size -- 10.2.5 Padding -- 10.3 Convolutional Layer Implementation -- 10.3.1 Custom Weights -- 10.3.2 Convolutional Layer Classes -- 10.4 Hands-On LeNet-5 -- 10.5 Representation Learning -- 10.6 Gradient Propagation -- 10.7 Pooling Layer -- 10.8 BatchNorm Layer -- 10.8.1 Forward Propagation -- 10.8.2 Backward Propagation -- 10.8.3 Implementation of BatchNormalization layer -- 10.9 Classical Convolutional Network -- 10.9.1 AlexNet -- 10.9.2 VGG Series -- 10.9.3 GoogLeNet -- 10.10 Hands-On CIFAR10 and VGG13 -- 10.11 Convolutional Layer Variants -- 10.11.1 Dilated/Atrous Convolution -- 10.11.2 Transposed Convolution -- o + 2p − k = n * s -- o + 2p − k ≠n * s -- Matrix Transposition -- Transposed Convolution Implementation -- 10.11.3 Separate Convolution…”

“…In addition, the Wolfram language will be used as part of the deep machine learning demonstrations. A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. …”

“…The book begins by explaining how to set up the development environment. …”

“…Beginning data structures and algorithms in C sharp…”

“…The Azure IoT Edge platform uses many existing technologies that may be familiar to developers, but understanding how to leverage those technologies in an edge computing scenario can be challenging. Beginning Azure IoT Edge Computing demystifies computing on the edge and explains, through concrete examples and exercises, how and when to leverage the power of intelligent edge computing. …”

“…Beginning Office three hundred and sixty-five collaboration apps…”

“…Implement machine learning models in your iOS applications. This short work begins by reviewing the primary principals of machine learning and then moves on to discussing more advanced topics, such as CoreML, the framework used to enable machine learning tasks in Apple products. …”