Data Science and Machine Learning: From Data to Knowledge

by Michele di Nuzzo

Extracting knowledge from information through data analysis: the data scientist has been called the most attractive profession of the 21st century. Analyze the relationships between data, discover new information and, thanks to machine learning, exploit the immense potential hidden in it by building predictive models. In this book, we illustrate methods to analyze and manipulate data, and Machine Learning and Deep Learning algorithms to predict information, moving from theoretical knowledge to practical applications with statistical software R, through extensive practical examplesWhat you will learnMathematics and algebra for machine learningStatistics and probability for data scienceUse of the statistical software R and R-StudioData preparation and feature engineeringDesign and validate machine learning algorithmsRegression, classification and clustering algorithmsMaking predictions based on time seriesThe models of neural networks and deep learningData visualization & data storytellingWho this book is forThis book is for anyone who wants to learn how to manipulate and analyze data by drawing new knowledge from it. If you are an IT manager or an analyst who wants to enter the world of Data Science and Big Data, if you are a developer who wants to know the new trends in the field of Artificial Intelligence or you are simply curious about this world, then this book is for you.ContentsData science and analysis modelsBig data managementUnivariate and multivariate analysis, probability and hypothesis testingExploring and visualizing dataData preparation and data cleaningSupervised classification and regressionUnsupervised clustering and dimensionality reductionSemi-Supervised LearningAssociation algorithms and time series analysisValidation measures and algorithms optimizationNeural networks and Deep LearningConvolutional networks for image recognitionRecurrent Networks and LSMT for sequencesEncoders for feature selectionGenerative algorithms

482 pages, Kindle Edition

Published December 11, 2021