Learning Core Audio A Hands-On Guide to Audio Programming for Mac and iOS 英文无水印pdf pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 本资源转载自网络，如有侵权，请联系上传者或csdn删除

Shaders need shader model 3.0+, hands also looks pretty at standard and mobile shaders. PBR Arms and Hands for female and male characters in standalone and mobile versions.. Assets use our custom and fast standard skin shader which supported features like: Translucency, Tint, Rim light, Ramp. With smart sliders you are able to control every aspect of the shader. Skin shader could be also used for other parts of character as basic skin shader. Models are animated and they contains pack of basic animations like: catching, throwing, fist fighting, idle, 3 spells, sword/knife fighting, pistol shooting. This pack contains: - Female and male arms for first person games in standalone and mobile versions. - Female and male hands for VR games in standalone and mobile versions. - All textures in 3 variants - Blood and Dirt support - Controllers for left and right hand/arms - 16 Animations for Arms - 21 Animations for Hands - Standard PBR skin shader - Test models: pistol and sword - Example and test system to control your hands and arms - Example and test VR and FP characters - Mecanim controllers for each hand - 35 Arms and hands textures (4096x4096) - 3 Ramp textures (256x16)

by Stefan Jansen Packt Publishing 2018-12-31 684 pages Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features Implement machine learning algorithms to build, train, and validate algorithmic models Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description 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. What you will learn Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems.

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Gain insight into how hexagonal architecture can help to keep the cost of development low over the complete lifetime of an application Key Features Explore ways to make your software flexible, extensible, and adaptable Learn new concepts that you can easily blend with your own software development style Develop the mindset of building maintainable solutions instead of taking shortcuts Book Description We would all like to build software architecture that yields adaptable and flexible software with low development costs. But, unreasonable deadlines and shortcuts make it very hard to create such an architecture. Get Your Hands Dirty on Clean Architecture starts with a discussion about the conventional layered architecture style and its disadvantages. It also talks about the advantages of the domain-centric architecture styles of Robert C. Martin's Clean Architecture and Alistair Cockburn's Hexagonal Architecture. Then, the book dives into hands-on chapters that show you how to manifest a hexagonal architecture in actual code. You'll learn in detail about different mapping strategies between the layers of a hexagonal architecture and see how to assemble the architecture elements into an application. The later chapters demonstrate how to enforce architecture boundaries. You'll also learn what shortcuts produce what types of technical debt and how, sometimes, it is a good idea to willingly take on those debts. After reading this book, you'll have all the knowledge you need to create applications using the hexagonal architecture style of web development. What you will learn Identify potential shortcomings of using a layered architecture Apply methods to enforce architecture boundaries Find out how potential shortcuts can affect the software architecture Produce arguments for when to use which style of architecture Structure your code according to the architecture Apply various types of tests that will cover each element of the architecture Who this

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Hands-On With AngularJS Using ASP.NET

《机器学习实战: 基于Scikit-Learn和Tensorflow》的高清英文带书签原版

高清、英文原版，美国亚马逊排名第一的tensorflow学习指导书籍，销量最好，评价五星！