Zero to Hero in Cryptocurrency Trading. Learn to trade on a centralized exchange, understand trading psychology, and implement a trading algorithm

Bogdan Vaida

In today's fast-paced digital age, cryptocurrencies have emerged as a revolutionary financial asset class, capturing the attention of investors and traders worldwide. However, navigating the world of cryptocurrency trading can be overwhelming for beginners. Zero to Hero in Cryptocurrency Trading acts as a guiding light to navigate this complex realm.This comprehensive guide to cryptocurrency trading empowers you to go from a novice trader to a proficient investor by helping you implement your own trading strategy. As you progress, you’ll gain structured trading knowledge through hands-on examples and real-time scenarios, bolstered by trading psychology and money management techniques. You’ll be able to automate your manual trades with an algorithm that works even while you sleep. You’ll also benefit from interactive teaching methods, including screenshots, charts, and drawings to help decode market operations and craft your unique edge in the dynamic crypto world. As an added bonus, you’ll receive ready-to-use templates to identify useful indicators, test your strategy, and even maintain a trading journal.By the end of this book, you’ll be well-equipped to trade cryptocurrencies and automate manual trading to give you an edge in the markets.

Node.js 6.x Blueprints. Maximize the potential of Node.js with real-world projects

Fernando Monteiro

Node.js is the most popular framework to create server-side applications today. Be it web, desktop, or mobile, Node.js comes to your rescue to create stunning real-time applications. Node.js 6.x Blueprints will teach you to build these types of projects in an easy-to-understand manner.The key to any Node.js project is a strong foundation on the concepts that will be a part of every project. The book will first teach you the MVC design pattern while developing a Twitter-like application using Express.js. In the next chapters, you will learn to create a website and applications such as streaming, photography, and a store locator using MongoDB, MySQL, and Firebase. Once you’re warmed up, we’ll move on to more complex projects such as a consumer feedback app, a real-time chat app, and a blog using Node.js with frameworks such as loopback.io and socket.io. Finally, we’ll explore front-end build processes, Docker, and continuous delivery.By the end of book, you will be comfortable working with Node.js applications and will know the best tools and frameworks to build highly scalable desktop and cloud applications.

Learning iBeacon

Craig Gilchrist

Hands-On Deep Learning with Go. A practical guide to building and implementing neural network models using Go

Gareth Seneque, Darrell Chua

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

Learn Kubernetes Security. Securely orchestrate, scale, and manage your microservices in Kubernetes deployments

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.

Deep Learning with TensorFlow. Explore neural networks and build intelligent systems with Python - Second Edition

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.

The Regularization Cookbook. Explore practical recipes to improve the functionality of your ML models

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.