Informatyka
Jaiprakash Pandey, Yasser Shoukry
AutoCAD is one of the most versatile software applications for architectural and engineering designs and the most popular computer-aided design (CAD) platform for 2D drafting and 3D modeling. This hands-on 2nd edition guide will take you through everything you need to know to make the most out of this powerful tool, from a simple tour of the user interface to using advanced tools.Starting with basic drawing shapes and functions, you'll get to grips with the fundamentals of CAD designs. You’ll then learn about effective drawing management using layers, dynamic blocks, and groups, and discover how to add annotations and plots like a professional. As you progress, the book will show you how to convert your 2D drawings into 3D models and shapes. You’ll also discover advanced features, such as isometric drawings, drawing utilities for managing and recovering complex files, quantity surveying, and multidisciplinary drawing files using xRefs. Finally, you’ll focus on rendering and visualizing your designs in AutoCAD.By the end of this book, you’ll have developed a solid understanding of CAD principles and be able to work with AutoCAD software confidently to build impressive 2D and 3D creations.
Salil Ajgaonkar
With the huge amount of data being generated over the internet and the benefits that Machine Learning (ML) predictions bring to businesses, ML implementation has become a low-hanging fruit that everyone is striving for. The complex mathematics behind it, however, can be discouraging for a lot of users. This is where H2O comes in – it automates various repetitive steps, and this encapsulation helps developers focus on results rather than handling complexities.You’ll begin by understanding how H2O’s AutoML simplifies the implementation of ML by providing a simple, easy-to-use interface to train and use ML models. Next, you’ll see how AutoML automates the entire process of training multiple models, optimizing their hyperparameters, as well as explaining their performance. As you advance, you’ll find out how to leverage a Plain Old Java Object (POJO) and Model Object, Optimized (MOJO) to deploy your models to production. Throughout this book, you’ll take a hands-on approach to implementation using H2O that’ll enable you to set up your ML systems in no time.By the end of this H2O book, you’ll be able to train and use your ML models using H2O AutoML, right from experimentation all the way to production without a single need to understand complex statistics or data science.
Mitesh Soni
Amazon Web Services (AWS) dominates the public cloud market by a huge margin and continues to be the first choice for many organizations. Networking has been an area of focus for all the leading cloud service providers. AWS has a suite of network-related products which help in performing network related task on AWS.This book initially covers the basics of networking in AWS. Then we use AWS VPC to create an isolated virtual cloud for performing network-related tasks. We then provide an overview of AWS Direct Connect after taking a deep dive into scalability and load balancing using the auto scaling feature, Elastic Load Balancing, and Amazon Route S3. Toward the end of the book, we cover troubleshooting tips and security best practices for your network. By the end of this book, you will have hands-on experience of working with network tasks on AWS.
Nataraj Dasgupta
Big Data analytics relates to the strategies used by organizations to collect, organize, and analyze large amounts of data to uncover valuable business insights that cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization’s data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages, and BI tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology and the practical reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB, and even learn how to write R code for neural networks.By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using the different tools and methods articulatedin this book.
Jim Sinur, Zbigniew Misiak, BJ Biernatowski, Pedro...
Every business transformation begins with one question, “How can we do this better?” Whether it’s eliminating inefficiencies, optimizing business operations, or reimagining entire workflows with the help of AI, success depends on understanding and optimizing business processes. However, finding the right approach can be challenging with shifting market demands and evolving technologies.In this book, three seasoned experts in BPM, automation, and AI-driven process optimization guide you through frameworks, techniques, and tools that drive digital transformation by helping you explore business process modelling, before and after process execution. You'll visualize complex workflows, establish scalable process architectures that drive digital transformation, and integrate automation for efficiency. With insights into BPMN, business value analysis, and field-tested consulting guidance, you'll see how process-led design and data-driven decisions can lead to smarter, more agile operations. Through real-world examples, you’ll grasp how leading organizations have optimized their processes and how you can apply the same principles in your digital change program.By the end of this book, you’ll be able to identify, design, analyze, and transform business processes for measurable impact, as well as master the synergy of technology, process, and strategy to build systems that drive sustainable growth.*Email sign-up and proof of purchase required
Matt Eland, Kevin Griffin
Too many C# developers feel stuck building the same apps day in and day out, but learning through side projects can reignite your passion and level up your skills. This book offers a practical, hands-on approach to building confidence with .NET 10 and modern C# by building a variety of engaging applications, from interactive games and productivity tools to machine learning apps and browser-based chatbots.These projects are designed to teach practical patterns and modern tooling, with a focus on learning and experimentation over production hardening. You'll work with tools like Spectre.Console, ML.NET, Uno Platform, and more, developing everything from an adventure game and a card tracker to an AI chatbot. You’ll also build modern AI-enabled systems using Ollama, Microsoft Agent Framework, OpenTelemetry, and Aspire.Written by an experienced C# engineer and teacher, this book blends technical depth with a developer-friendly tone, helping you learn faster and retain more. You'll sharpen your understanding of core .NET capabilities and gain confidence to apply them in your own work or hobby projects.By the end of this book, you'll not only have a portfolio of practical .NET apps - you’ll also have grown as a developer and rediscovered the joy of programming.*Email sign-up and proof of purchase required
Practical Convolutional Neural Networks. Implement advanced deep learning models using Python
Mohit Sewak, Md. Rezaul Karim, Pradeep Pujari
Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available.Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets.
Ed Moyle, Diana Kelley
Cybersecurity architects work with others to develop a comprehensive understanding of the business' requirements. They work with stakeholders to plan designs that are implementable, goal-based, and in keeping with the governance strategy of the organization.With this book, you'll explore the fundamentals of cybersecurity architecture: addressing and mitigating risks, designing secure solutions, and communicating with others about security designs. The book outlines strategies that will help you work with execution teams to make your vision a concrete reality, along with covering ways to keep designs relevant over time through ongoing monitoring, maintenance, and continuous improvement. As you progress, you'll also learn about recognized frameworks for building robust designs as well as strategies that you can adopt to create your own designs.By the end of this book, you will have the skills you need to be able to architect solutions with robust security components for your organization, whether they are infrastructure solutions, application solutions, or others.