Automated Deep Learning Using Neural Network Intelligence
Optimize, develop, and design PyTorch and TensorFlow models for a specific problem using the Microsoft Neural Network Intelligence (NNI) toolkit. This book includes practical examples illustrating automated deep learning approaches and provides techniques to facilitate your deep learning model development. The first chapters of this book cover the basics of NNI toolkit usage and methods for solving hyper-parameter optimization tasks. You will understand the black-box function maximization problem using NNI, and know how to prepare a TensorFlow or PyTorch model for hyper-parameter tuning, launch an experiment, and interpret the results. The book dives into optimization tuners and the search algorithms they are based on: Evolution search, Annealing search, and the Bayesian Optimization approach. The Neural Architecture Search is covered and you will learn how to develop deep learning models from scratch. Multi-trial and one-shot searching approaches of automatic neural network design ...
Optimize, develop, and design PyTorch and TensorFlow models for a specific problem using the Microsoft Neural Network Intelligence (NNI) toolkit. This book includes practical examples illustrating automated deep learning approaches and provides techniques to facilitate your deep learning model development. The first chapters of this book cover the basics of NNI toolkit usage and methods for solving hyper-parameter optimization tasks. You will understand the black-box function maximization problem using NNI, and know how to prepare a TensorFlow or PyTorch model for hyper-parameter tuning, launch an experiment, and interpret the results. The book dives into optimization tuners and the search algorithms they are based on: Evolution search, Annealing search, and the Bayesian Optimization approach. The Neural Architecture Search is covered and you will learn how to develop deep learning models from scratch. Multi-trial and one-shot searching approaches of automatic neural network design ...
Secret Key Cryptography
Secret Key Cryptography gives you a toolbox of cryptographic techniques and Secret Key methods. The book's simple, non-technical language is easy to understand and accessible for any reader, even without the advanced mathematics normally required for cryptography. You'll learn how to create and solve ciphers, as well as how to measure their strength. As you go, you'll explore both historic ciphers and groundbreaking new approaches - including a never-before-seen way to implement the uncrackable One-Time Pad algorithm. Whoever you are, this book is for you! History buffs will love seeing the evolution of sophisticated cryptographic methods, hobbyists will get a gentle introduction to cryptography, and engineers and computer scientists will learn the principles of constructing secure ciphers. Even professional cryptographers will find a range of new methods and concepts never published before. From the Roman empire's Caesar cipher to the WWII Enigma machine, secret messages have in ...
Secret Key Cryptography gives you a toolbox of cryptographic techniques and Secret Key methods. The book's simple, non-technical language is easy to understand and accessible for any reader, even without the advanced mathematics normally required for cryptography. You'll learn how to create and solve ciphers, as well as how to measure their strength. As you go, you'll explore both historic ciphers and groundbreaking new approaches - including a never-before-seen way to implement the uncrackable One-Time Pad algorithm. Whoever you are, this book is for you! History buffs will love seeing the evolution of sophisticated cryptographic methods, hobbyists will get a gentle introduction to cryptography, and engineers and computer scientists will learn the principles of constructing secure ciphers. Even professional cryptographers will find a range of new methods and concepts never published before. From the Roman empire's Caesar cipher to the WWII Enigma machine, secret messages have in ...
3D Deep Learning with Python
With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time. Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library. By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. ...
With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time. Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library. By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. ...
Practical MATLAB Deep Learning, 2nd Edition
Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning. Over the course of the book, you'll learn to model complex systems and apply deep learning to problems in those areas. Applications include: Aircraft navigation; An aircraft that lands on Titan, the moon of Saturn, using reinforcement learning; Stock market prediction; Natural language processing; Music creation usng generative deep learning; Plasma control; Earth sensor processing for spacecraft; MATLAB Bluetooth data acquisition applied to dance physics. ...
Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning. Over the course of the book, you'll learn to model complex systems and apply deep learning to problems in those areas. Applications include: Aircraft navigation; An aircraft that lands on Titan, the moon of Saturn, using reinforcement learning; Stock market prediction; Natural language processing; Music creation usng generative deep learning; Plasma control; Earth sensor processing for spacecraft; MATLAB Bluetooth data acquisition applied to dance physics. ...
Learning Tableau 2022, 5th Edition
Learning Tableau 2022 helps you get started with Tableau and data visualization, but it does more than just cover the basic principles. It helps you understand how to analyze and communicate data visually, and articulate data stories using advanced features. This new edition is updated with Tableau's latest features, such as dashboard extensions, Explain Data, and integration with CRM Analytics (Einstein Analytics), which will help you harness the full potential of artificial intelligence (AI) and predictive modeling in Tableau. After an exploration of the core principles, this book will teach you how to use table and level of detail calculations to extend and alter default visualizations, build interactive dashboards, and master the art of telling stories with data. You'll learn about visual statistical analytics and create different types of static and animated visualizations and dashboards for rich user experiences. We then move on to interlinking different data sources wit ...
Learning Tableau 2022 helps you get started with Tableau and data visualization, but it does more than just cover the basic principles. It helps you understand how to analyze and communicate data visually, and articulate data stories using advanced features. This new edition is updated with Tableau's latest features, such as dashboard extensions, Explain Data, and integration with CRM Analytics (Einstein Analytics), which will help you harness the full potential of artificial intelligence (AI) and predictive modeling in Tableau. After an exploration of the core principles, this book will teach you how to use table and level of detail calculations to extend and alter default visualizations, build interactive dashboards, and master the art of telling stories with data. You'll learn about visual statistical analytics and create different types of static and animated visualizations and dashboards for rich user experiences. We then move on to interlinking different data sources wit ...
Deep Learning for Natural Language Processing
Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You'll learn to use ...
Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You'll learn to use ...
Productionizing AI
This book is a guide to productionizing AI solutions using best-of-breed cloud services with workarounds to lower costs. Supplemented with step-by-step instructions covering data import through wrangling to partitioning and modeling through to inference and deployment, and augmented with plenty of Python code samples, the book has been written to accelerate the process of moving from script or notebook to app. From an initial look at the context and ecosystem of AI solutions today, the book drills down from high-level business needs into best practices, working with stakeholders, and agile team collaboration. From there you'll explore data pipeline orchestration, machine and deep learning, including working with and finding shortcuts using artificial neural networks such as AutoML and AutoAI. You'll also learn about the increasing use of NoLo UIs through AI application development, industry case studies, and finally a practical guide to deploying containerized AI solutions. The b ...
This book is a guide to productionizing AI solutions using best-of-breed cloud services with workarounds to lower costs. Supplemented with step-by-step instructions covering data import through wrangling to partitioning and modeling through to inference and deployment, and augmented with plenty of Python code samples, the book has been written to accelerate the process of moving from script or notebook to app. From an initial look at the context and ecosystem of AI solutions today, the book drills down from high-level business needs into best practices, working with stakeholders, and agile team collaboration. From there you'll explore data pipeline orchestration, machine and deep learning, including working with and finding shortcuts using artificial neural networks such as AutoML and AutoAI. You'll also learn about the increasing use of NoLo UIs through AI application development, industry case studies, and finally a practical guide to deploying containerized AI solutions. The b ...
Learning JavaScript Design Patterns, 2nd Edition
Do you want to write beautiful, structured, and maintainable JavaScript by applying modern design patterns to the language? Do you want clean, efficient, manageable code? Want to stay up-to-date with the latest best practices? If so, the updated second edition of Learning JavaScript Design Patterns is the ideal place to start. Author Addy Osmani shows you how to apply modern design patterns to JavaScript and React - including modules, mixins, observers, and mediators. You'll learn about performance and rendering patterns such as server-side rendering and Islands architecture. You'll also learn how architectural patterns like MVC, MVP, and MVVM are useful from the perspective of a modern web application developer. This book explores: Architectural patterns for structuring your components and apps; More than 20 design patterns in JavaScript and React, applicable for developers at any level; Different pattern categories including creational, structural, and behavioral; Essential per ...
Do you want to write beautiful, structured, and maintainable JavaScript by applying modern design patterns to the language? Do you want clean, efficient, manageable code? Want to stay up-to-date with the latest best practices? If so, the updated second edition of Learning JavaScript Design Patterns is the ideal place to start. Author Addy Osmani shows you how to apply modern design patterns to JavaScript and React - including modules, mixins, observers, and mediators. You'll learn about performance and rendering patterns such as server-side rendering and Islands architecture. You'll also learn how architectural patterns like MVC, MVP, and MVVM are useful from the perspective of a modern web application developer. This book explores: Architectural patterns for structuring your components and apps; More than 20 design patterns in JavaScript and React, applicable for developers at any level; Different pattern categories including creational, structural, and behavioral; Essential per ...
Statistical Learning and Sequential Prediction
This free book will focus on theoretical aspects of Statistical Learning and Sequential Prediction. Until recently, these two subjects have been treated separately within the learning community. The course will follow a unified approach to analyzing learning in both scenarios. To make this happen, we shall bring together ideas from probability and statistics, game theory, algorithms, and optimization. It is this blend of ideas that makes the subject interesting for us, and we hope to convey the excitement. We shall try to make the course as self-contained as possible, and pointers to additional readings will be provided whenever necessary. Our target audience is graduate students with a solid background in probability and linear algebra. ...
This free book will focus on theoretical aspects of Statistical Learning and Sequential Prediction. Until recently, these two subjects have been treated separately within the learning community. The course will follow a unified approach to analyzing learning in both scenarios. To make this happen, we shall bring together ideas from probability and statistics, game theory, algorithms, and optimization. It is this blend of ideas that makes the subject interesting for us, and we hope to convey the excitement. We shall try to make the course as self-contained as possible, and pointers to additional readings will be provided whenever necessary. Our target audience is graduate students with a solid background in probability and linear algebra. ...
Design for Learning
Our purpose in this book is twofold. First, we introduce the basic skill set and knowledge base used by practicing instructional designers. We do this through chapters contributed by experts in the field who have either academic, research-based backgrounds, or practical, on-the-job experience (or both). Our goal is that students in introductory instructional design courses will be able to use this book as a guide for completing a basic instructional design project. We also hope the book is useful as a ready resource for more advanced students or others seeking to develop their instructional design knowledge and skills. Our second purpose complements the first: to introduce instructional designers to some of the most current views on how the practices of design thinking contribute towards the development of effective and engaging learning environments. While some previous books have incorporated elements of design thinking (for example, processes like prototyping), to date no instruc ...
Our purpose in this book is twofold. First, we introduce the basic skill set and knowledge base used by practicing instructional designers. We do this through chapters contributed by experts in the field who have either academic, research-based backgrounds, or practical, on-the-job experience (or both). Our goal is that students in introductory instructional design courses will be able to use this book as a guide for completing a basic instructional design project. We also hope the book is useful as a ready resource for more advanced students or others seeking to develop their instructional design knowledge and skills. Our second purpose complements the first: to introduce instructional designers to some of the most current views on how the practices of design thinking contribute towards the development of effective and engaging learning environments. While some previous books have incorporated elements of design thinking (for example, processes like prototyping), to date no instruc ...