Mike Roshak Ph.D

Artificial intelligence (AI) is rapidly finding practical applications across a wide variety of industry verticals, and the Internet of Things (IoT) is one of them. Developers are looking for ways to make IoT devices smarter and to make users' lives easier. With this AI cookbook, you'll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions, along with covering advanced AI techniques that facilitate analytics and learning in various… Show more

Artificial intelligence (AI) is rapidly finding practical applications across a wide variety of industry verticals, and the Internet of Things (IoT) is one of them. Developers are looking for ways to make IoT devices smarter and to make users' lives easier. With this AI cookbook, you'll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions, along with covering advanced AI techniques that facilitate analytics and learning in various IoT applications.

Using a recipe-based approach, the book will take you through essential processes such as data collection, data analysis, modeling, statistics and monitoring, and deployment. You'll use real-life datasets from smart homes, industrial IoT, and smart devices to train and evaluate simple to complex models and make predictions using trained models. Later chapters will take you through the key challenges faced while implementing machine learning, deep learning, and other AI techniques, such as natural language processing (NLP), computer vision, and embedded machine learning for building smart IoT systems. In addition to this, you'll learn how to deploy models and improve their performance with ease.

By the end of this book, you'll be able to package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems.

What you will learn
Explore various AI techniques to build smart IoT solutions from scratch
Use machine learning and deep learning techniques to build smart voice recognition and facial detection systems
Gain insights into IoT data using algorithms and implement them in projects
Perform anomaly detection for time series data and other types of IoT data
Implement embedded systems learning techniques for machine learning on small devices
Apply pre-trained machine learning models to an edge device
Deploy machine learning models to web apps and mobile using TensorFlow.js and Java Show less

Cloud computing has revolutionized the way many organizations operate. Although there are many advantages to using cloud computing, research indicates that cloud computing is not always beneficial. Cloud computing research shows can be marred with issues such as network latency, inflexibility, and challenges to software implementation. While other research shows that cloud computing can benefit projects by decreasing initial cost and providing scalability. The triple constraint of time, scope,… Show more

Cloud computing has revolutionized the way many organizations operate. Although there are many advantages to using cloud computing, research indicates that cloud computing is not always beneficial. Cloud computing research shows can be marred with issues such as network latency, inflexibility, and challenges to software implementation. While other research shows that cloud computing can benefit projects by decreasing initial cost and providing scalability. The triple constraint of time, scope, and cost also known as critical success factors (CSF), have been shown to be predictors of project success. This study compares the time, scope, and cost of projects that incorporate cloud computing to determine if issues such as the different software development paradigm of cloud computing impacts projects. Using a Likert study of 80 individuals in the software development industry who have used cloud computing, this study shows that projects utilizing cloud computing tend to be smaller in scope, cost less, and are faster to implement. Show less