Видавець: K-i-s-publishing
Giuseppe Ciaburro
Keras 2.x Projects explains how to leverage the power of Keras to build and train state-of-the-art deep learning models through a series of practical projects that look at a range of real-world application areas. To begin with, you will quickly set up a deep learning environment by installing the Keras library. Through each of the projects, you will explore and learn the advanced concepts of deep learning and will learn how to compute and run your deep learning models using the advanced offerings of Keras. You will train fully-connected multilayer networks, convolutional neural networks, recurrent neural networks, autoencoders and generative adversarial networks using real-world training datasets. The projects you will undertake are all based on real-world scenarios of all complexity levels, covering topics such as language recognition, stock volatility, energy consumption prediction, faster object classification for self-driving vehicles, and more. By the end of this book, you will be well versed with deep learning and its implementation with Keras. You will have all the knowledge you need to train your own deep learning models to solve different kinds of problems.
Keras 3. Comprehensive Insights into Keras for Deep Learning and AI Solutions
Rheinwerk Publishing, Inc, Mohammad Nauman
This book provides a comprehensive guide to mastering deep learning with Keras 3, starting from the fundamentals of machine learning and neural networks to advanced techniques in reinforcement learning, transformers, and generative AI. Readers will begin with understanding the core principles of machine learning, including supervised, unsupervised, and reinforcement learning. The book explains how neural networks function and how to build them using Keras, TensorFlow, and Python. You'll dive into critical topics such as convolutional neural networks (CNNs), dropout regularization, and gradient descent optimization. As you progress, you’ll learn advanced deep learning concepts like transfer learning, transformers, and the powerful Keras Functional API for building complex models. There’s a focus on practical applications, such as building and evaluating deep learning models for real-world tasks, and enhancing models using GPU acceleration. You'll also explore generative models, including autoencoders and GANs, and apply them to tasks like image generation and data augmentation. By the end of the book, you’ll be able to implement state-of-the-art AI models and deploy them in production environments.
Keras Deep Learning Cookbook. Over 30 recipes for implementing deep neural networks in Python
Rajdeep Dua, Manpreet Singh Ghotra
Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy.The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks. By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning
Giuseppe Ciaburro, Sudharsan Ravichandiran, Suriyadeepan Ramamoorthy
Reinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks. Keras Reinforcement Learning Projects installs human-level performance into your applications using algorithms and techniques of reinforcement learning, coupled with Keras, a faster experimental library.The book begins with getting you up and running with the concepts of reinforcement learning using Keras. You’ll learn how to simulate a random walk using Markov chains and select the best portfolio using dynamic programming (DP) and Python. You’ll also explore projects such as forecasting stock prices using Monte Carlo methods, delivering vehicle routing application using Temporal Distance (TD) learning algorithms, and balancing a Rotating Mechanical System using Markov decision processes.Once you’ve understood the basics, you’ll move on to Modeling of a Segway, running a robot control system using deep reinforcement learning, and building a handwritten digit recognition model in Python using an image dataset. Finally, you’ll excel in playing the board game Go with the help of Q-Learning and reinforcement learning algorithms.By the end of this book, you’ll not only have developed hands-on training on concepts, algorithms, and techniques of reinforcement learning but also be all set to explore the world of AI.
Stian Thorgersen, Pedro Igor Silva
Implementing authentication and authorization for applications can be a daunting experience, often leaving them exposed to security vulnerabilities. Keycloak is an open-source solution for identity management and access management for modern applications, which can make a world of difference if you learn how to use it. Keycloak, helping you get started with using it and securing your applications. Complete with hands-on tutorials, best practices, and self-assessment questions, this easy-to-follow guide will show you how to secure a sample application and then move on to securing different application types. As you progress, you will understand how to configure and manage Keycloak as well as how to leverage some of its more advanced capabilities. Finally, you'll gain insights into securely using Keycloak in production.By the end of this book, you will have learned how to install and manage Keycloak as well as how to secure new and existing applications.
Stian Thorgersen, Pedro Igor Silva
The second edition of Keycloak - Identity and Access Management for Modern Applications is an updated, comprehensive introduction to Keycloak and its updates.In this new edition, you will learn how to use the latest distribution of Keycloak. The recent versions of Keycloak are now based on Quarkus, which brings a new and improved user experience and a new admin console with a higher focus on usability. You will see how to leverage Spring Security, instead of the Keycloak Spring adapter while using Keycloak 22. As you progress, you’ll understand the new Keycloak distribution and explore best practices in using OAuth. Finally, you'll cover general best practices and other information on how to protect your applications.By the end of this new edition, you’ll have learned how to install and manage the latest version of Keycloak to secure new and existing applications using the latest features.
Jei Lee Jo
Creating realistic images has been always a meticulous process where setting up the stage is a long and complicated task. KeyShot has simplified this process by allowing us to have a greater amount of control and flexibility in all aspects of the rendering procedure.KeyShot 3D Rendering provides a series of exercises with a detailed explanation of each part of the pipeline, from importing our model, to texturing, lighting, and rendering. In addition, the book covers in detail how to use all the necessary parameters inside KeyShot and also explains alternative methods to showcase your work.KeyShot 3D Rendering starts with covering all the basic principles and fundamentals of how to work and navigate in KeyShot. Throughout the book, there will be exercises that will guide and help you to complete the chapter's assignment. Also there will be an explanation of all the terms and parameters used in the exercises.You will learn how to use HDRIs (High Dynamic Range Images) as the primary source for lighting and also how to incorporate backplate images into a scene. You will learn how to create your own materials, textures, and labels. Lastly this book covers camera functions, real-time settings to improve the workflow of your assignments, and also rendering properties.The exercises in the book will provide you with all the tools necessary to bring your models to life and set up your own environment. You will learn how to adjust overall properties accordingly to maximize rendering output.
Kibana 7 Quick Start Guide. Visualize your Elasticsearch data with ease
Anurag Srivastava
The Elastic Stack is growing rapidly and, day by day, additional tools are being added to make it more effective. This book endeavors to explain all the important aspects of Kibana, which is essential for utilizing its full potential.This book covers the core concepts of Kibana, with chapters set out in a coherent manner so that readers can advance their learning in a step-by-step manner. The focus is on a practical approach, thereby enabling the reader to apply those examples in real time for a better understanding of the concepts and to provide them with the correct skills in relation to the tool. With its succinct explanations, it is quite easy for a reader to use this book as a reference guide for learning basic to advanced implementations of Kibana. The practical examples, such as the creation of Kibana dashboards from CSV data, application RDBMS data, system metrics data, log file data, APM agents, and search results, can provide readers with a number of different drop-off points from where they can fetch any type of data into Kibana for the purpose of analysis or dashboarding.