ISBN: 0262542528 9780262542524

Category: Computers / Data Science / Machine Learning

Page count: 280

<b>MIT presents a concise primer on machine learning—computer programs that learn from data and the basis of applications like voice recognition and driverless cars.</b><br> <b> </b><br> <b>No in-depth knowledge of math or programming required!</b><br>  <br> Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don’t yet use every day, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of “the new AI.” This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias.<br>  <br> Alpaydin explains that as Big Data has grown, the theory of machine learning—the foundation of efforts to process that data into knowledge—has also advanced. He covers:<br>  <br> • The evolution of machine learning<br> • Important learning algorithms and example applications<br> • Using machine learning algorithms for pattern recognition<br> • Artificial neural networks inspired by the human brain<br> • Algorithms that learn associations between instances<br> • Reinforcement learning<br> • Transparency, explainability, and fairness in machine learning<br> • The ethical and legal implicates of data-based decision making<br>  <br> A comprehensive introduction to machine learning, this book does not require any previous knowledge of mathematics or programming—making it accessible for everyday readers and easily adoptable for classroom syllabi.