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Machine Learning for Healthcare Analytics Projects - Build smart AI applications using neural network methodologies across the healthcare vertical market (Paperback)
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Machine Learning for Healthcare Analytics Projects - Build smart AI applications using neural network methodologies across the healthcare vertical market (Paperback)
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Create real-world machine learning solutions using NumPy, pandas,
matplotlib, and scikit-learn Key Features Develop a range of
healthcare analytics projects using real-world datasets Implement
key machine learning algorithms using a range of libraries from the
Python ecosystem Accomplish intermediate-to-complex tasks by
building smart AI applications using neural network methodologies
Book DescriptionMachine 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 (KNN) models. In the
final chapters, you will create a deep neural network in Keras to
predict the onset of diabetes in a huge dataset of patients. You
will also learn how to predict heart diseases using neural
networks. By the end of this book, you will have learned how to
address long-standing challenges, provide specialized solutions for
how to deal with them, and carry out a range of cognitive tasks in
the healthcare domain. What you will learn Explore super imaging
and natural language processing (NLP) to classify DNA sequencing
Detect cancer based on the cell information provided to the SVM
Apply supervised learning techniques to diagnose autism spectrum
disorder (ASD) Implement a deep learning grid and deep neural
networks for detecting diabetes Analyze data from blood pressure,
heart rate, and cholesterol level tests using neural networks Use
ML algorithms to detect autistic disorders Who this book is
forMachine Learning for Healthcare Analytics Projects is for data
scientists, machine learning engineers, and healthcare
professionals who want to implement machine learning algorithms to
build smart AI applications. Basic knowledge of Python or any
programming language is expected to get the most from this book.
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