Artificial Intelligence in Medical Sciences and Psychology
Get started with artificial intelligence for medical sciences and psychology. This book will help healthcare professionals and technologists solve problems using machine learning methods, computer vision, and natural language processing (NLP) techniques. The book covers ways to use neural networks to classify patients with diseases. You will know how to apply computer vision techniques and convolutional neural networks (CNNs) to segment diseases such as cancer (e.g., skin, breast, and brain cancer) and pneumonia. The hidden Markov decision making process is presented to help you identify hidden states of time-dependent data. In addition, it shows how NLP techniques are used in medical records classification. This book is suitable for experienced practitioners in varying medical specialties (neurology, virology, radiology, oncology, and more) who want to learn Python programming to help them work efficiently. It is also intended for data scientists, machine learning engineers, m ...
Get started with artificial intelligence for medical sciences and psychology. This book will help healthcare professionals and technologists solve problems using machine learning methods, computer vision, and natural language processing (NLP) techniques. The book covers ways to use neural networks to classify patients with diseases. You will know how to apply computer vision techniques and convolutional neural networks (CNNs) to segment diseases such as cancer (e.g., skin, breast, and brain cancer) and pneumonia. The hidden Markov decision making process is presented to help you identify hidden states of time-dependent data. In addition, it shows how NLP techniques are used in medical records classification. This book is suitable for experienced practitioners in varying medical specialties (neurology, virology, radiology, oncology, and more) who want to learn Python programming to help them work efficiently. It is also intended for data scientists, machine learning engineers, m ...
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 ...
Network Programming with Go Language, 2nd Edition
Dive into key topics in network architecture implemented with the Google-backed open source Go programming language. Networking topics such as data serialization, application level protocols, character sets and encodings are discussed and demonstrated in Go. This book has been updated to the Go version 1.18 which includes modules, generics, and fuzzing along with updated and additional examples. Beyond the fundamentals, Network Programming with Go, Second Edition covers key networking and security issues such as HTTP protocol changes, validation and templates, remote procedure call (RPC) and REST comparison, and more. Additionally, authors Ronald Petty and Jan Newmarch guide you in building and connecting to a complete web server based on Go. Along the way, use of a Go web toolkit (Gorilla) will be employed. This book can serve as both an essential learning guide and reference on networking concepts and implementation in Go. Free source code is available on Github for this book u ...
Dive into key topics in network architecture implemented with the Google-backed open source Go programming language. Networking topics such as data serialization, application level protocols, character sets and encodings are discussed and demonstrated in Go. This book has been updated to the Go version 1.18 which includes modules, generics, and fuzzing along with updated and additional examples. Beyond the fundamentals, Network Programming with Go, Second Edition covers key networking and security issues such as HTTP protocol changes, validation and templates, remote procedure call (RPC) and REST comparison, and more. Additionally, authors Ronald Petty and Jan Newmarch guide you in building and connecting to a complete web server based on Go. Along the way, use of a Go web toolkit (Gorilla) will be employed. This book can serve as both an essential learning guide and reference on networking concepts and implementation in Go. Free source code is available on Github for this book u ...
Database Design, 2nd Edition
Database Design, 2nd Edition covers database systems and database design concepts. New to this edition are SQL info, additional examples, key terms and review exercises at the end of each chapter. Topics include:The history of databases; Characteristics and benefits of databases; Data models; Data modelling; Classification of database management systems; Integrity rules and constraints; Functional dependencies; Normalization; Database development process. ...
Database Design, 2nd Edition covers database systems and database design concepts. New to this edition are SQL info, additional examples, key terms and review exercises at the end of each chapter. Topics include:The history of databases; Characteristics and benefits of databases; Data models; Data modelling; Classification of database management systems; Integrity rules and constraints; Functional dependencies; Normalization; Database development process. ...
Introduction to Game Design, Prototyping, and Development, 3rd Edition
A hands-on book that explains concepts "by doing," Introduction to Game Design, Prototyping, and Development, 3rd Edition, takes readers through the process of making both paper and digital game prototypes. Rather than focusing on a single tutorial, as most Unity books have done, this book explores several small prototypes, reinforcing critical concepts through repetition from project to project. Author Jeremy Gibson Bond's approach creates a stable of "base projects" that serve as starters for readers looking to create their own games), while skipping the aspects of project creation (e.g. modeling, animation, etc.) that are less central to this book. Intermediate readers may browse this book for a tutorial that clarifies the specific prototyping or programming concept that they wish to learn. This book begins with an introduction to general game design concepts and basic programing concepts. C# is the chosen language used in this book, and it is easy to learn and enforces good codi ...
A hands-on book that explains concepts "by doing," Introduction to Game Design, Prototyping, and Development, 3rd Edition, takes readers through the process of making both paper and digital game prototypes. Rather than focusing on a single tutorial, as most Unity books have done, this book explores several small prototypes, reinforcing critical concepts through repetition from project to project. Author Jeremy Gibson Bond's approach creates a stable of "base projects" that serve as starters for readers looking to create their own games), while skipping the aspects of project creation (e.g. modeling, animation, etc.) that are less central to this book. Intermediate readers may browse this book for a tutorial that clarifies the specific prototyping or programming concept that they wish to learn. This book begins with an introduction to general game design concepts and basic programing concepts. C# is the chosen language used in this book, and it is easy to learn and enforces good codi ...
A Network Architect's Guide to 5G
As 5G transforms mobile usage and services, network professionals will need to significantly evolve their transport network architectures towards greater sophistication and stronger integration with radio networks, and facilitate transition towards cloud-native 5G mobile core. Until now, however, most 5G guides have foregrounded RF/radio and mobile core innovations, not its implications for data networks. A Network Architects Guide to 5G fills the gap, giving network architects, designers, and engineers essential knowledge for designing and planning their own 5G networks. Drawing on decades of experience with global service providers and enterprise networks, the authors illuminate new and evolving network technologies necessary for building 5G-capable networks, such as segment routing, network slicing, timing and synchronization, edge computing, distributed data centers, integration with public cloud, and more. They explain how 5G blurs boundaries between mobile core, radio access, ...
As 5G transforms mobile usage and services, network professionals will need to significantly evolve their transport network architectures towards greater sophistication and stronger integration with radio networks, and facilitate transition towards cloud-native 5G mobile core. Until now, however, most 5G guides have foregrounded RF/radio and mobile core innovations, not its implications for data networks. A Network Architects Guide to 5G fills the gap, giving network architects, designers, and engineers essential knowledge for designing and planning their own 5G networks. Drawing on decades of experience with global service providers and enterprise networks, the authors illuminate new and evolving network technologies necessary for building 5G-capable networks, such as segment routing, network slicing, timing and synchronization, edge computing, distributed data centers, integration with public cloud, and more. They explain how 5G blurs boundaries between mobile core, radio access, ...
Even You Can Learn Statistics and Analytics, 4th Edition
This book discusses statistics and analytics using plain language and avoiding mathematical jargon. If you thought you couldnt learn these data analysis subjects because they were too technical or too mathematical, this book is for you! This edition delivers more everyday examples and end-of-chapter exercises and contains updated instructions for using Microsoft Excel. Youll use downloadable data sets and spreadsheet solutions, template-based solutions you can put right to work. Using this book, you will understand the important concepts of statistics and analytics, including learning the basic vocabulary of these subjects. Create tabular and visual summaries and learn to avoid common charting errors; Gain experience working with common descriptive statistics measures including the mean, median, and mode; and standard deviation and variance, among others; Understand the probability concepts that underlie inferential statistics; Learn how to apply hypothesis tests, using Z, t, chi ...
This book discusses statistics and analytics using plain language and avoiding mathematical jargon. If you thought you couldnt learn these data analysis subjects because they were too technical or too mathematical, this book is for you! This edition delivers more everyday examples and end-of-chapter exercises and contains updated instructions for using Microsoft Excel. Youll use downloadable data sets and spreadsheet solutions, template-based solutions you can put right to work. Using this book, you will understand the important concepts of statistics and analytics, including learning the basic vocabulary of these subjects. Create tabular and visual summaries and learn to avoid common charting errors; Gain experience working with common descriptive statistics measures including the mean, median, and mode; and standard deviation and variance, among others; Understand the probability concepts that underlie inferential statistics; Learn how to apply hypothesis tests, using Z, t, chi ...
Algorithmic Aspects of Machine Learning
This course is organized around algorithmic issues that arise in machine learning. Modern machine learning systems are often built on top of algorithms that do not have provable guarantees, and it is the subject of debate when and why they work. In this class, we focus on designing algorithms whose performance we can rigorously analyze for fundamental machine learning problems. The book is based on the class "Algorithmic Aspects of Machine Learning" taught at MIT in Fall 2013, Spring 2015 and Fall 2017. ...
This course is organized around algorithmic issues that arise in machine learning. Modern machine learning systems are often built on top of algorithms that do not have provable guarantees, and it is the subject of debate when and why they work. In this class, we focus on designing algorithms whose performance we can rigorously analyze for fundamental machine learning problems. The book is based on the class "Algorithmic Aspects of Machine Learning" taught at MIT in Fall 2013, Spring 2015 and Fall 2017. ...
Machine Learning on Kubernetes
MLOps is an emerging field that aims to bring repeatability, automation, and standardization of the software engineering domain to data science and machine learning engineering. By implementing MLOps with Kubernetes, data scientists, IT professionals, and data engineers can collaborate and build machine learning solutions that deliver business value for their organization. You'll begin by understanding the different components of a machine learning project. Then, you'll design and build a practical end-to-end machine learning project using open source software. As you progress, you'll understand the basics of MLOps and the value it can bring to machine learning projects. You will also gain experience in building, configuring, and using an open source, containerized machine learning platform. In later chapters, you will prepare data, build and deploy machine learning models, and automate workflow tasks using the same platform. Finally, the exercises in this book will help you get han ...
MLOps is an emerging field that aims to bring repeatability, automation, and standardization of the software engineering domain to data science and machine learning engineering. By implementing MLOps with Kubernetes, data scientists, IT professionals, and data engineers can collaborate and build machine learning solutions that deliver business value for their organization. You'll begin by understanding the different components of a machine learning project. Then, you'll design and build a practical end-to-end machine learning project using open source software. As you progress, you'll understand the basics of MLOps and the value it can bring to machine learning projects. You will also gain experience in building, configuring, and using an open source, containerized machine learning platform. In later chapters, you will prepare data, build and deploy machine learning models, and automate workflow tasks using the same platform. Finally, the exercises in this book will help you get han ...
Becoming an Enterprise Django Developer
Django is a powerful framework but choosing the right add-ons that match the scale and scope of your enterprise projects can be tricky. This book will help you explore the multifarious options available for enterprise Django development. Countless organizations are already using Django and more migrating to it, unleashing the power of Python with many different packages and dependencies, including AI technologies. This practical guide will help you understand practices, blueprints, and design decisions to put Django to work the way you want it to. You'll learn various ways in which data can be rendered onto a page and discover the power of Django for large-scale production applications. Starting with the basics of getting an enterprise project up and running, you'll get to grips with maintaining the project throughout its lifecycle while learning what the Django application lifecycle is. By the end of this book, you'll have learned how to build and deploy a Django project to the ...
Django is a powerful framework but choosing the right add-ons that match the scale and scope of your enterprise projects can be tricky. This book will help you explore the multifarious options available for enterprise Django development. Countless organizations are already using Django and more migrating to it, unleashing the power of Python with many different packages and dependencies, including AI technologies. This practical guide will help you understand practices, blueprints, and design decisions to put Django to work the way you want it to. You'll learn various ways in which data can be rendered onto a page and discover the power of Django for large-scale production applications. Starting with the basics of getting an enterprise project up and running, you'll get to grips with maintaining the project throughout its lifecycle while learning what the Django application lifecycle is. By the end of this book, you'll have learned how to build and deploy a Django project to the ...