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Podcasty
The increasing growth in blockchain use is enormous, and it is changing the way business is done. Many leading organizations are already exploring the potential of blockchain. With this book, you will learn to build end-to-end enterprise-level decentralized applications and scale them across your organization to meet your company's needs. This book will help you understand what DApps are and how the blockchain ecosystem works, via real-world examples. This extensive end-to-end book covers every blockchain aspect for business and for developers. You will master process flows and incorporate them into your own enterprise. You will learn how to use J.P. Morgan’s Quorum to build blockchain-based applications. You will also learn how to write applications that can help communicate enterprise blockchain solutions. You will learn how to write smart contracts that run without censorship and third-party interference.Once you've grasped what a blockchain is and have learned about Quorum, you will jump into building real-world practical blockchain applications for sectors such as payment and money transfer, healthcare, cloud computing, supply chain management, and much more.
C++ is a general-purpose programming language with a bias toward system programming as it provides ready access to hardware-level resources, efficient compilation, and a versatile approach to higher-level abstractions.This book will help you understand the benefits of system programming with C++17. You will gain a firm understanding of various C, C++, and POSIX standards, as well as their respective system types for both C++ and POSIX. After a brief refresher on C++, Resource Acquisition Is Initialization (RAII), and the new C++ Guideline Support Library (GSL), you will learn to program Linux and Unix systems along with process management. As you progress through the chapters, you will become acquainted with C++'s support for IO. You will then study various memory management methods, including a chapter on allocators and how they benefit system programming. You will also explore how to program file input and output and learn about POSIX sockets. This book will help you get to grips with safely setting up a UDP and TCP server/client.Finally, you will be guided through Unix time interfaces, multithreading, and error handling with C++ exceptions. By the end of this book, you will be comfortable with using C++ to program high-quality systems.
Predictive analytics discovers hidden patterns from structured and unstructured data for automated decision making in business intelligence. Predictive decisions are becoming a huge trend worldwide, catering to wide industry sectors by predicting which decisions are more likely to give maximum results. TensorFlow, Google’s brainchild, is immensely popular and extensively used for predictive analysis.This book is a quick learning guide on all the three types of machine learning, that is, supervised, unsupervised, and reinforcement learning with TensorFlow. This book will teach you predictive analytics for high-dimensional and sequence data. In particular, you will learn the linear regression model for regression analysis. You will also learn how to use regression for predicting continuous values. You will learn supervised learning algorithms for predictive analytics. You will explore unsupervised learning and clustering using K-meansYou will then learn how to predict neighborhoods using K-means, and then, see another example of clustering audio clips based on their audio features. This book is ideal 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. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. This book is repurposed for this specific learning experience from material from Packt's Predictive Analytics with TensorFlow by Md. Rezaul Karim.
Spatial Analytics with ArcGIS. Build powerful insights with spatial analytics
Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis.The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data.
Carol Fairchild, Dr. Thomas L. Harman
ROS is a robust robotics framework that works regardless of hardware architecture or hardware origin. It standardizes most layers of robotics functionality from device drivers to process control and message passing to software package management. But apart from just plain functionality, ROS is a great platform to learn about robotics itself and to simulate, as well as actually build, your first robots. This does not mean that ROS is a platform for students and other beginners; on the contrary, ROS is used all over the robotics industry to implement flying, walking and diving robots, yet implementation is always straightforward, and never dependent on the hardware itself.ROS Robotics has been the standard introduction to ROS for potential professionals and hobbyists alike since the original edition came out; the second edition adds a gradual introduction to all the goodness available with the Kinetic Kame release.By providing you with step-by-step examples including manipulator arms and flying robots, the authors introduce you to the new features. The book is intensely practical, with space given to theory only when absolutely necessary. By the end of this book, you will have hands-on experience on controlling robots with the best possible framework.
This hands-on tutorial, filled with exercises and examples, introduces the reader to a variety of concepts within Pentaho Reporting. With screenshots that show you how reports look at design time as well as how they should look when rendered as PDF, Excel, HTML, Text, Rich-Text-File, XML, and CSV, this book also contains complete example source code that you can copy and paste into your environment to get up-and-running quickly. Updated to cover the features of Pentaho 8, this book will teach you everything you need to know to build fast, efficient reports using Pentaho. If your interest lies in the technical details of creating reports and you want to see how to solve common reporting problems with a minimum of fuss, this is the book for you.
The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies.This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You’ll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies.Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym.
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.