Deep Belief Nets in C++ and CUDA C: Volume 3
Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a thought process that is capable of learning abstract concepts built from simpler primitives. These models are especially useful for image processing applications. At each step Deep Belief Nets in C++ and CUDA C: Volume 3 presents intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. Source code for all routines presented in the book, and the executable CONVNET program which implements these algorithms, are available for free download. Discover convolutional nets and how to use them; Build deep feedforward nets using locall ...
Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a thought process that is capable of learning abstract concepts built from simpler primitives. These models are especially useful for image processing applications. At each step Deep Belief Nets in C++ and CUDA C: Volume 3 presents intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. Source code for all routines presented in the book, and the executable CONVNET program which implements these algorithms, are available for free download. Discover convolutional nets and how to use them; Build deep feedforward nets using locall ...
Hands-On Intelligent Agents with OpenAI Gym
Many real-world problems can be broken down into tasks that require a series of decisions to be made or actions to be taken. The ability to solve such tasks without a machine being programmed requires a machine to be artificially intelligent and capable of learning to adapt. This book is an easy-to-follow guide to implementing learning algorithms for machine software agents in order to solve discrete or continuous sequential decision making and control tasks. Hands-On Intelligent Agents with OpenAI Gym takes you through the process of building intelligent agent algorithms using deep reinforcement learning starting from the implementation of the building blocks for configuring, training, logging, visualizing, testing, and monitoring the agent. You will walk through the process of building intelligent agents from scratch to perform a variety of tasks. In the closing chapters, the book provides an overview of the latest learning environments and learning algorithms, along with pointers ...
Many real-world problems can be broken down into tasks that require a series of decisions to be made or actions to be taken. The ability to solve such tasks without a machine being programmed requires a machine to be artificially intelligent and capable of learning to adapt. This book is an easy-to-follow guide to implementing learning algorithms for machine software agents in order to solve discrete or continuous sequential decision making and control tasks. Hands-On Intelligent Agents with OpenAI Gym takes you through the process of building intelligent agent algorithms using deep reinforcement learning starting from the implementation of the building blocks for configuring, training, logging, visualizing, testing, and monitoring the agent. You will walk through the process of building intelligent agents from scratch to perform a variety of tasks. In the closing chapters, the book provides an overview of the latest learning environments and learning algorithms, along with pointers ...
Hands-On Deep Learning for Images with TensorFlow
TensorFlow is Google's popular offering for machine learning and deep learning, quickly becoming a favorite tool for performing fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations of real-world projects, teaching you how to leverage TensorFlow's capabilities to perform efficient image processing using the power of deep learning. With the help of this book, you will get to grips with the different paradigms of performing deep learning such as deep neural nets and convolutional neural networks, followed by understanding how they can be implemented using TensorFlow. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow and Keras. ...
TensorFlow is Google's popular offering for machine learning and deep learning, quickly becoming a favorite tool for performing fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations of real-world projects, teaching you how to leverage TensorFlow's capabilities to perform efficient image processing using the power of deep learning. With the help of this book, you will get to grips with the different paradigms of performing deep learning such as deep neural nets and convolutional neural networks, followed by understanding how they can be implemented using TensorFlow. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow and Keras. ...
Hands-On Convolutional Neural Networks with TensorFlow
Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time! We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation. After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks. Later on, you will see useful tips ...
Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time! We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation. After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks. Later on, you will see useful tips ...
Delphi Cookbook, 3rd Edition
Delphi is a cross-platform integrated development environment (IDE) that supports rapid application development on different platforms, saving you the pain of wandering amid GUI widget details or having to tackle inter-platform incompatibilities. Delphi Cookbook begins with the basics of Delphi and gets you acquainted with JSON format strings, XSLT transformations, Unicode encodings, and various types of streams. You'll then move on to more advanced topics such as developing higher-order functions and using enumerators and run-time type information (RTTI). As you make your way through the chapters, you'll understand Delphi RTL functions, use FireMonkey in a VCL application, and cover topics such as multithreading, using aparallel programming library and deploying Delphi on a server. You'll take a look at the new feature of WebBroker Apache modules, join the mobile revolution with FireMonkey, and learn to build data-driven mobile user interfaces using the FireDAC database access fram ...
Delphi is a cross-platform integrated development environment (IDE) that supports rapid application development on different platforms, saving you the pain of wandering amid GUI widget details or having to tackle inter-platform incompatibilities. Delphi Cookbook begins with the basics of Delphi and gets you acquainted with JSON format strings, XSLT transformations, Unicode encodings, and various types of streams. You'll then move on to more advanced topics such as developing higher-order functions and using enumerators and run-time type information (RTTI). As you make your way through the chapters, you'll understand Delphi RTL functions, use FireMonkey in a VCL application, and cover topics such as multithreading, using aparallel programming library and deploying Delphi on a server. You'll take a look at the new feature of WebBroker Apache modules, join the mobile revolution with FireMonkey, and learn to build data-driven mobile user interfaces using the FireDAC database access fram ...
Hands-On Security in DevOps
DevOps has provided speed and quality benefits with continuous development and deployment methods, but it does not guarantee the security of an entire organization. Hands-On Security in DevOps shows you how to adopt DevOps techniques to continuously improve your organization's security at every level, rather than just focusing on protecting your infrastructure. This guide combines DevOps and security to help you to protect cloud services, and teaches you how to use techniques to integrate security directly in your product. You will learn how to implement security at every layer, such as for the web application, cloud infrastructure, communication, and the delivery pipeline layers. With the help of practical examples, you'll explore the core security aspects, such as blocking attacks, fraud detection, cloud forensics, and incident response. In the concluding chapters, you will cover topics on extending DevOps security, such as risk assessment, threat modeling, and continuous security ...
DevOps has provided speed and quality benefits with continuous development and deployment methods, but it does not guarantee the security of an entire organization. Hands-On Security in DevOps shows you how to adopt DevOps techniques to continuously improve your organization's security at every level, rather than just focusing on protecting your infrastructure. This guide combines DevOps and security to help you to protect cloud services, and teaches you how to use techniques to integrate security directly in your product. You will learn how to implement security at every layer, such as for the web application, cloud infrastructure, communication, and the delivery pipeline layers. With the help of practical examples, you'll explore the core security aspects, such as blocking attacks, fraud detection, cloud forensics, and incident response. In the concluding chapters, you will cover topics on extending DevOps security, such as risk assessment, threat modeling, and continuous security ...
R Deep Learning Essentials, 2nd Edition
Deep learning is a powerful subset of machine learning that is very successful in domains such as computer vision and natural language processing (NLP). This second edition of R Deep Learning Essentials will open the gates for you to enter the world of neural networks by building powerful deep learning models using the R ecosystem. This book will introduce you to the basic principles of deep learning and teach you to build a neural network model from scratch. As you make your way through the book, you will explore deep learning libraries, such as Keras, MXNet, and TensorFlow, and create interesting deep learning models for a variety of tasks and problems, including structured data, computer vision, text data, anomaly detection, and recommendation systems. You'll cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud. In the concluding chapters, you will learn about the theoretical concepts of deep learning ...
Deep learning is a powerful subset of machine learning that is very successful in domains such as computer vision and natural language processing (NLP). This second edition of R Deep Learning Essentials will open the gates for you to enter the world of neural networks by building powerful deep learning models using the R ecosystem. This book will introduce you to the basic principles of deep learning and teach you to build a neural network model from scratch. As you make your way through the book, you will explore deep learning libraries, such as Keras, MXNet, and TensorFlow, and create interesting deep learning models for a variety of tasks and problems, including structured data, computer vision, text data, anomaly detection, and recommendation systems. You'll cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud. In the concluding chapters, you will learn about the theoretical concepts of deep learning ...
Angular Design Patterns
This book is an insightful journey through the most valuable design patterns, and it will provide clear guidance on how to use them effectively in Angular. You will explore some of the best ways to work with Angular and how to use it to meet the stability and performance required in today's web development world. You'll get to know some Angular best practices to improve your productivity and the code base of your application. We will take you on a journey through Angular designs for the real world, using a combination of case studies, design patterns to follow, and anti-patterns to avoid. By the end of the book, you will understand the various features of Angular, and will be able to apply well-known, industry-proven design patterns in your work. ...
This book is an insightful journey through the most valuable design patterns, and it will provide clear guidance on how to use them effectively in Angular. You will explore some of the best ways to work with Angular and how to use it to meet the stability and performance required in today's web development world. You'll get to know some Angular best practices to improve your productivity and the code base of your application. We will take you on a journey through Angular designs for the real world, using a combination of case studies, design patterns to follow, and anti-patterns to avoid. By the end of the book, you will understand the various features of Angular, and will be able to apply well-known, industry-proven design patterns in your work. ...
Thoughtful Data Science
Thoughtful Data Science brings new strategies and a carefully crafted programmer's toolset to work with modern, cutting-edge data analysis. This new approach is designed specifically to give developers more efficiency and power to create cutting-edge data analysis and artificial intelligence insights. Industry expert David Taieb bridges the gap between developers and data scientists by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust. You'll find the right balance of strategic thinking and practical projects throughout this book, with extensive code files and Jupyter projects that you can integrate with your own data analysis. David Taieb introduces four projects designed to connect developers to important industry use cases in data science. The first is an image recognition application with TensorFlow, to meet the growing importance of AI in data analysis. The second analyses social media trends to explore big data issues and na ...
Thoughtful Data Science brings new strategies and a carefully crafted programmer's toolset to work with modern, cutting-edge data analysis. This new approach is designed specifically to give developers more efficiency and power to create cutting-edge data analysis and artificial intelligence insights. Industry expert David Taieb bridges the gap between developers and data scientists by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust. You'll find the right balance of strategic thinking and practical projects throughout this book, with extensive code files and Jupyter projects that you can integrate with your own data analysis. David Taieb introduces four projects designed to connect developers to important industry use cases in data science. The first is an image recognition application with TensorFlow, to meet the growing importance of AI in data analysis. The second analyses social media trends to explore big data issues and na ...
Mastering Functional Programming
In large projects, it can get difficult keeping track of all the interdependencies of the code base and how its state changes at runtime. Functional Programming helps us solve these problems. It is a paradigm specifically designed to deal with the complexity of software development. This book will show you how the right abstractions can reduce complexity and make your code easy to read and understand. Mastering Functional Programming begins by touching upon the basics such as what lambdas are and how to write declarative code with the help of functions. It then moves on to more advanced concepts such as pure functions and type classes, the problems they aim to solve, and how to use them in real-world scenarios. You will also explore some of the more advanced patterns in the world of functional programming, such as monad transformers and Tagless Final. In the concluding chapters, you will be introduced to the actor model, implement it in modern functional languages, and explore the s ...
In large projects, it can get difficult keeping track of all the interdependencies of the code base and how its state changes at runtime. Functional Programming helps us solve these problems. It is a paradigm specifically designed to deal with the complexity of software development. This book will show you how the right abstractions can reduce complexity and make your code easy to read and understand. Mastering Functional Programming begins by touching upon the basics such as what lambdas are and how to write declarative code with the help of functions. It then moves on to more advanced concepts such as pure functions and type classes, the problems they aim to solve, and how to use them in real-world scenarios. You will also explore some of the more advanced patterns in the world of functional programming, such as monad transformers and Tagless Final. In the concluding chapters, you will be introduced to the actor model, implement it in modern functional languages, and explore the s ...