Items related to Fundamentals of Machine Learning using Python
Synopsis
Fundamentals of Machine Learning discusses the basics of python, use of python in computing and provides a general outlook on machine learning. This book provides an insight into concepts such as linear regression with one variable, linear algebra, and linear regression with multiple inputs. The classification with logistics regression model, regularization, neural networks, decision trees are explained in this book. The introduction to several concepts of machine learning such as component analysis, classification using k-Nearest Algorithm, k Means Clustering, computing with Tensor flow and natural language processing have been explained. This book explains the fundamental concepts of machine learning.
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About the Author
Euan Russano was born in Minas Gerais, Brazil. He is a Chemical Engineer since 2012 by the Rural University of Rio de Janeiro (UFRRJ). He obtained his Msc. in 2014 at UFRRJ, in the area of Chemical Engineering, with specializazion in Process Control. In 2014, Russano began to develop his PhD at the University Duisburg-Essen (UDE) in the field of Water Science. His carrer was initiated in a Petrobras project in the Polymers Laboratory, at UFRRJ. From 2012 to 2014 he worked in the Fluids Flow Laboratory (Petrobras/ UFRRJ) with oil well pressure control. Since 2014 he works as an research assistant at the University of Duisburg-Essen, with water systems identification and control.
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