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Podcasts
Go is an open source programming language designed by Google for handling large-scale projects efficiently. The Go ecosystem comprises some really powerful deep learning tools such as DQN and CUDA. With this book, you'll be able to use these tools to train and deploy scalable deep learning models from scratch. This deep learning book begins by introducing you to a variety of tools and libraries available in Go. It then takes you through building neural networks, including activation functions and the learning algorithms that make neural networks tick. In addition to this, you'll learn how to build advanced architectures such as autoencoders, restricted Boltzmann machines (RBMs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and more. You'll also understand how you can scale model deployments on the AWS cloud infrastructure for training and inference. By the end of this book, you'll have mastered the art of building, training, and deploying deep learning models in Go to solve real-world problems.
Dart: Scalable Application Development. Provides a solid foundation of libraries and tools
David Mitchell, Sergey Akopkokhyants, Ivo Balbaert
Designed to create next generation apps, Google’s Dart offers a much more robust framework and also supersedes JavaScript in several aspects. Familiar yet innovative, compact yet scalable, it blows away the accumulated JavaScript legacy limitations. Dart was designed for great tool-ability and developer productivity, allowing you to create better application faster than before. Google chose it for their billion dollar advertising business and you have its power for your projects too.The first module will introduce you the Dart language starting from its conception to its current form, and where it headed is through engaging substantial practical projects. You will be taken through building typical applications and exploring the exciting new technologies of HTML5.The second module will show you how to add internalization support to your web applications and how i18n and i10n access can be embedded into your code to design applications that can be localized easily. You will be shown how to organize client-to-server communication and how different HTML5 features can be used in Dart. Finally, this module will show you how you can store data locally, break the storage limit, and prevent security issues in your web application.The third module is a pragmatic guide that will increase your expertise in writing all kinds of applications, including web apps, scripts, and server-side apps. It provides rich insights on how to extend your Dart programming skills. Altogether, this course provides you the power to create powerful applications with Dart, without worrying about your knowledge leading to you having to make compromises to the end product!This Learning Path has been curated from three Packt products:Dart By Example By Davy MitchellMastering Dart By Sergey AkopkokhyantsDart Cookbook By Ivo Balbaert
Kaizhe Huang, Pranjal Jumde, Loris Degioanni
Kubernetes is an open source orchestration platform for managing containerized applications. Despite widespread adoption of the technology, DevOps engineers might be unaware of the pitfalls of containerized environments. With this comprehensive book, you'll learn how to use the different security integrations available on the Kubernetes platform to safeguard your deployments in a variety of scenarios.Learn Kubernetes Security starts by taking you through the Kubernetes architecture and the networking model. You'll then learn about the Kubernetes threat model and get to grips with securing clusters. Throughout the book, you'll cover various security aspects such as authentication, authorization, image scanning, and resource monitoring. As you advance, you'll learn about securing cluster components (the kube-apiserver, CoreDNS, and kubelet) and pods (hardening image, security context, and PodSecurityPolicy). With the help of hands-on examples, you'll also learn how to use open source tools such as Anchore, Prometheus, OPA, and Falco to protect your deployments.By the end of this Kubernetes book, you'll have gained a solid understanding of container security and be able to protect your clusters from cyberattacks and mitigate cybersecurity threats.
Giancarlo Zaccone, Md. Rezaul Karim
Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks.This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. Throughout the book, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way.You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects.
Vincent Vandenbussche, Akin Osman Kazakci
Regularization is an infallible way to produce accurate results with unseen data, however, applying regularization is challenging as it is available in multiple forms and applying the appropriate technique to every model is a must. The Regularization Cookbook provides you with the appropriate tools and methods to handle any case, with ready-to-use working codes as well as theoretical explanations. After an introduction to regularization and methods to diagnose when to use it, you’ll start implementing regularization techniques on linear models, such as linear and logistic regression, and tree-based models, such as random forest and gradient boosting. You’ll then be introduced to specific regularization methods based on data, high cardinality features, and imbalanced datasets. In the last five chapters, you’ll discover regularization for deep learning models. After reviewing general methods that apply to any type of neural network, you’ll dive into more NLP-specific methods for RNNs and transformers, as well as using BERT or GPT-3. By the end, you’ll explore regularization for computer vision, covering CNN specifics, along with the use of generative models such as stable diffusion and Dall-E.By the end of this book, you’ll be armed with different regularization techniques to apply to your ML and DL models.
Mike Oryszak, Michael C Oryszak
SharePoint is an incredibly powerful platform that can support a wide variety of business scenarios. In many cases it needs to be configured or extended in order to deliver fully featured business solutions.While some books merely talk about the capabilities of SharePoint in general and leave you to figure out how they apply to your situation, this book takes a different approach. Each chapter provides easy-to-understand, step-by-step instructions along with screenshots to help build exciting SharePoint business solutions that extend the platform. By the end of this book the reader will be a SharePoint developer to be reckoned with.This book will dive into a diverse set of real-world scenarios to deliver sample business solutions that can serve as the foundation for your own solutions. This book draws from the author's extensive experience with SharePoint to leverage the platforms underlying services to provide solutions that can support Social Collaboration, Content and Document Management, as well as project collaboration. Each chapter represents a new business solution that builds on the overall platform to deliver more complex solutions and more advanced techniques. By the end of the book the reader will understand how to leverage the SharePoint platform to build their own business solutions.
A Blueprint for Production-Ready Web Applications will help you expand upon your coding knowledge and teach you how to create a complete web application. Unlike other guides that focus solely on a singular technology or process, this book shows you how to combine different technologies and processes as needed to meet industry standards.You’ll begin by learning how to set up your development environment, and use Quart and React to create the backend and frontend, respectively. This book then helps you get to grips with managing and validating accounts, structuring relational tables, and creating forms to manage data. As you progress through the chapters, you’ll gain a comprehensive understanding of web application development by creating a to-do app, which can be used as a base for your future projects. Finally, you’ll find out how to deploy and monitor your application, along with discovering advanced concepts such as managing database migrations and adding multifactor authentication.By the end of this web development book, you’ll be able to apply the lessons and industry best practices that you’ve learned to both your personal and work projects, allowing you to further develop your coding portfolio.
GNS3, Christopher J Welsh (USD)
GNS3 is an open-source Graphical Network Simulator used extensively by networking professionals to simulate networking devices such as Cisco, Juniper and Vyatta routers, along with Virtual PCs.GNS3 Network Simulation Guide gives you all the information you need to run a successful GNS3 simulation. You will be guided through the tricky installation pre-requisites and procedures involved in developing a simulated topology suitable for studying for Cisco CCIE Certification. We will also cover many useful tips and tricks which will help you make the most of your GNS3 simulator application.You will begin the GNS3 journey by ensuring that you have prepared your computer with any additional files required by GNS3, to set up the simulated environment needed for a successful installation process.Once GNS3 is installed, you will get to work creating a successful simulation including routers, Ethernet switches, Virtual PCs, and capture packets using Wireshark. Next, you will learn how to master GNS3's Graphical User Interface as well as the Command Console. The inner workings of GNS3 are described in depth so that you gain an appreciation of how UDP tunnels are used to tie the many components of GNS3 together.By following the clear examples and exercises in this guide, you will learn everything that you need to know about how to use GNS3 to prepare for certifications, as well as simulate real-world network scenarios.