Machine Learning for Healthcare Analytics Projects
Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics. This book will teach you how to implement key machine learning algorithms and walk you through their use cases by employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors ( ...
Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics. This book will teach you how to implement key machine learning algorithms and walk you through their use cases by employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors ( ...
Hands-On Machine Learning with Azure
Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way. The book begins by covering the benefits of ML and AI in the cloud. You will then explore Microsoft's Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications.This book lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The book then takes you through a preconfigured series of virtual machines in Azure targeted at AI developme ...
Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way. The book begins by covering the benefits of ML and AI in the cloud. You will then explore Microsoft's Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications.This book lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The book then takes you through a preconfigured series of virtual machines in Azure targeted at AI developme ...
Python Deep Learning Projects
Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system. Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects. By the end of ...
Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system. Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects. By the end of ...
Machine Learning in Java, 2nd Edition
As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge. Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11. Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analy ...
As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge. Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11. Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analy ...
Machine Learning with AWS
Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are highly scalable. From natural language processing (NLP) applications, such as language translation and understanding news articles and other text sources, to creating chatbots with both voice and text interfaces, you will learn all that there is to know about using AWS to your advantage. You will also understand how to process huge numbers of images fast and create machine learning models. By the end of this book, you will have developed the skills you need to efficiently use AWS in your machine learning and artificial intelligence projects. ...
Machine Learning with AWS is the right place to start if you are a beginner interested in learning useful artificial intelligence (AI) and machine learning skills using Amazon Web Services (AWS), the most popular and powerful cloud platform. You will learn how to use AWS to transform your projects into apps that work at high speed and are highly scalable. From natural language processing (NLP) applications, such as language translation and understanding news articles and other text sources, to creating chatbots with both voice and text interfaces, you will learn all that there is to know about using AWS to your advantage. You will also understand how to process huge numbers of images fast and create machine learning models. By the end of this book, you will have developed the skills you need to efficiently use AWS in your machine learning and artificial intelligence projects. ...
Machine Learning Fundamentals
As machine learning algorithms become popular, new tools that optimize these algorithms are also developed. Machine Learning Fundamentals explains you how to use the syntax of scikit-learn. You'll study the difference between supervised and unsupervised models, as well as the importance of choosing the appropriate algorithm for each dataset. You'll apply unsupervised clustering algorithms over real-world datasets, to discover patterns and profiles, and explore the process to solve an unsupervised machine learning problem. The focus of the book then shifts to supervised learning algorithms. You'll learn to implement different supervised algorithms and develop neural network structures using the scikit-learn package. You'll also learn how to perform coherent result analysis to improve the performance of the algorithm by tuning hyperparameters. By the end of this book, you will have gain all the skills required to start programming machine learning algorithms. ...
As machine learning algorithms become popular, new tools that optimize these algorithms are also developed. Machine Learning Fundamentals explains you how to use the syntax of scikit-learn. You'll study the difference between supervised and unsupervised models, as well as the importance of choosing the appropriate algorithm for each dataset. You'll apply unsupervised clustering algorithms over real-world datasets, to discover patterns and profiles, and explore the process to solve an unsupervised machine learning problem. The focus of the book then shifts to supervised learning algorithms. You'll learn to implement different supervised algorithms and develop neural network structures using the scikit-learn package. You'll also learn how to perform coherent result analysis to improve the performance of the algorithm by tuning hyperparameters. By the end of this book, you will have gain all the skills required to start programming machine learning algorithms. ...
Full Stack JavaScript, 2nd Edition
Learn agile JavaScript web development using the latest cutting-edge front-end and back-end technologies including Node.js, MongoDB, Backbone.js, Parse.com, Heroku, and Microsoft Azure. Using a key project example of a message board app, you will learn the foundations of a typical web application: fetching data, displaying it, and submitting new data. Practical examples of the app build are provided with multiple technologies and all code examples are in full color. This book will save you many hours by providing a hand-picked and tested collection of quick start guides that will enable you to spend less time learning and more time building your own applications. Completely updated for this second edition, Full Stack JavaScript uses current versions of all technologies, including ES6/ES2015 and the latest versions of Node and npm. Prototype fast and ship code that matters! Use a collection of quick start guides, tutorials, and suggestions, to enhance several development apps; Rev ...
Learn agile JavaScript web development using the latest cutting-edge front-end and back-end technologies including Node.js, MongoDB, Backbone.js, Parse.com, Heroku, and Microsoft Azure. Using a key project example of a message board app, you will learn the foundations of a typical web application: fetching data, displaying it, and submitting new data. Practical examples of the app build are provided with multiple technologies and all code examples are in full color. This book will save you many hours by providing a hand-picked and tested collection of quick start guides that will enable you to spend less time learning and more time building your own applications. Completely updated for this second edition, Full Stack JavaScript uses current versions of all technologies, including ES6/ES2015 and the latest versions of Node and npm. Prototype fast and ship code that matters! Use a collection of quick start guides, tutorials, and suggestions, to enhance several development apps; Rev ...
Scaling Your Node.js Apps
Take your Node.js application into production-ready status, capable of scaling up to whatever your needs might be. You'll discover that architecting for successful, popular sites is an essential tool of any professional Node.js developer, and learning to scale your own applications is a great place to start. Using this book you will learn when to scale, what factors should trigger scaling, and what architectural techniques are best suited for scaling. You will also explore common pitfalls that arise when scaling a Node.js application and solutions to correct them. Including analyses of success cases at the largest-scale companies, such as Netflix and Paypal, this book will get you started with scaling in no time at all. Determine what factors should trigger the need to scale; Discover different architectural patterns that lend themselves to scaling; Resolve problems that arise when scaling up a Node.js application; Monitor a platform in order to understand when to start scali ...
Take your Node.js application into production-ready status, capable of scaling up to whatever your needs might be. You'll discover that architecting for successful, popular sites is an essential tool of any professional Node.js developer, and learning to scale your own applications is a great place to start. Using this book you will learn when to scale, what factors should trigger scaling, and what architectural techniques are best suited for scaling. You will also explore common pitfalls that arise when scaling a Node.js application and solutions to correct them. Including analyses of success cases at the largest-scale companies, such as Netflix and Paypal, this book will get you started with scaling in no time at all. Determine what factors should trigger the need to scale; Discover different architectural patterns that lend themselves to scaling; Resolve problems that arise when scaling up a Node.js application; Monitor a platform in order to understand when to start scali ...
Go Machine Learning Projects
Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured. The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate m ...
Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured. The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate m ...
Testing Vue.js Applications
Testing Vue.js Applications is a comprehensive guide to testing Vue components, methods, events, and output. Author Edd Yerburgh, creator of the Vue testing utility, explains the best testing practices in Vue along with an evergreen methodology that applies to any web dev process. Web developers who use the Vue framework love its reliability, speed, small footprint, and versatility. Vue's component-based approach and use of DOM methods require you to adapt your app-testing practices. Learning Vue-specific testing tools and strategies will ensure your apps run like they should. With Testing Vue.js Applications, you'll discover effective testing methods for Vue applications. You'll enjoy author Edd Yerburgh's engaging style and fun real-world examples as you learn to use the Jest framework to run tests for a Hacker News application built with Vue, Vuex, and Vue Router. This comprehensive guide teaches the best testing practices in Vue along with an evergreen methodology that applie ...
Testing Vue.js Applications is a comprehensive guide to testing Vue components, methods, events, and output. Author Edd Yerburgh, creator of the Vue testing utility, explains the best testing practices in Vue along with an evergreen methodology that applies to any web dev process. Web developers who use the Vue framework love its reliability, speed, small footprint, and versatility. Vue's component-based approach and use of DOM methods require you to adapt your app-testing practices. Learning Vue-specific testing tools and strategies will ensure your apps run like they should. With Testing Vue.js Applications, you'll discover effective testing methods for Vue applications. You'll enjoy author Edd Yerburgh's engaging style and fun real-world examples as you learn to use the Jest framework to run tests for a Hacker News application built with Vue, Vuex, and Vue Router. This comprehensive guide teaches the best testing practices in Vue along with an evergreen methodology that applie ...