Practical Application Development with AppRunExplore the concepts, patterns, and architecture behind AppRun applications. With this end-to-end guide, you will be able to build web apps fast to the market with the low learning curve and high development productivity.
You will learn how to break down the application logic into three decoupled parts: state, view, and update. You will then see how to connect web page events to the AppRun event life-cycle, route user interactions, access data from the remote servers, compose the user interface using components, and integrate 3rd party libraries.
Following examples of various apps, such as the counter app, to-do app, weather app, hacker news reader app, and blog app, you will have all the techniques for developing your AppRun apps including the line of business apps. You will also review wider development concepts such as using strongly typed states practically, unit testing strategies for app state changes, time travel debugging, async web API invocation, server-side virtual DO ...
MATLAB Machine Learning Recipes, 2nd EditionHarness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more.
How to write code for machine learning, adaptive control and estimation using MATLAB; How these three areas complement each other; How these three areas are needed for robust machine learning applications; How to use MATLAB graphics and visualization tools for machine learning; How to code real world examples in MATLAB for major applications of ...
Python: Beginner's Guide to Artificial IntelligenceThis Learning Path offers practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. You will be introduced to various machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. You'll find a new balance of classical ideas and modern insights into machine learning. You will learn to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open-source Python libraries.
Throughout the Learning Path, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, and Autoencoders. Discover how to attain deep learning programming on GPU in a distributed way.
By the end of this Learning Path, you know the fundamentals of AI and have worked through a n ...
Deployment of Microsoft Azure Cloud SolutionsMicrosoft Azure has numerous effective solutions that shape the future of any business. Over the years, Azure cloud services have grown quickly, and the number of organizations adopting Azure for their cloud services is also gradually increasing. Leading industry giants are finding that Azure fulfills their extensive cloud requirements.
Deployment of Microsoft Azure Cloud Solutions starts with an extensive introduction to all the categories of designs available with Azure. These design patterns focus on different aspects of the cloud such as high availability, data management, and so on.
You will learn various aspects such as building your cloud structure and architecture. You will also have a brief understanding of the different types of services provided by Azure, such as Azure functions and Azure Analytics, which can prove beneficial for an organization. You will learn each and every aspect and function required to develop an Azure cloud based on your organizational requiremen ...
Serverless Architectures with AWSServerless Architecture with AWS begins with an introduction to the serverless model and helps you get started with AWS and Lambda. You'll also get to grips with other capabilities of the AWS Serverless Platform and see how AWS supports enterprise-grade serverless applications with and without Lambda.
This book will guide you in deploying your first serverless project and exploring the capabilities of serverless Amazon Athena, an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (S3 Amazon) using standard SQL. You'll also learn about AWS Glue, a fully managed ETL service that makes categorizing data easy and cost-effective. You'll study how Amazon Kinesis makes it possible to unleash the potential of real-time data insights and analytics with capabilities such as video streams, data streams, data firehose, and data analytics. Last but not least, you'll be equipped to combine Amazon Kinesis capabilities with AWS Lambda to create lightweight ...
Command Line FundamentalsThe most basic interface to a computer - the command line - remains the most flexible and powerful way of processing data and performing and automating various day-to-day tasks.
Command Line Fundamentals begins by exploring the basics, and then focuses on the most common tool, the Bash shell (which is standard on all Linux and iOS systems). As you make your way through the book, you'll explore the traditional Unix command-line programs as implemented by the GNU project. You'll also learn to use redirection and pipelines to assemble these programs to solve complex problems.
By the end of this book, you'll have explored the basics of shell scripting, allowing you to easily and quickly automate tasks. ...
Learn Type-Driven DevelopmentType-driven development is an approach that uses a static type system to achieve results including safety and efficiency. Types are used to express relationships and other assumptions directly in the code, and these assumptions are enforced by the compiler before the code is run. Learn Type-Driven Development covers how to use these type systems to check the logical consistency of your code.
This book begins with the basic idea behind type-driven development. You'll learn about values (or terms) and how they contrast with types. As you progress through the chapters, you'll cover how to combine types and values inside modules and build structured types out of simpler ones. You'll then understand how to express choices or alternatives directly in the type system using variants, polymorphic variants, and generalized algebraic data types. You'll also get to grips with sum types, build sophisticated data types from generics, and explore functions that express change in the types of value ...
Julia Programming ProjectsJulia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing.
After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI.
Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After ...
Bayesian Analysis with Python, 2nd EditionThe 2nd edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models.
The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others.
By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After reading the book you will be better prepared to delve into more advanced material or specialized statistical modeling if you need to. ...
Azure PowerShell Quick Start GuideAs an IT professional, it is important to keep up with cloud technologies and learn to manage those technologies. PowerShell is a critical tool that must be learned in order to effectively and more easily manage many Azure resources. This book is designed to teach you to leverage PowerShell to enable you to perform many day-to-day tasks in Microsoft Azure.
Taking you through the basic tasks of installing Azure PowerShell and connecting to Azure, you will learn to properly connect to an Azure tenant with PowerShell. Next, you will dive into tasks such as deploying virtual machines with PowerShell, resizing them, and managing their power states with PowerShell.
Then, you will learn how to complete more complex Azure tasks with PowerShell, such as deploying virtual machines from custom images, creating images from existing virtual machines, and creating and managing of data disks. Later, you will learn how to snapshot virtual machines, how to encrypt virtual machines, and how to lev ...