Effective Amazon Machine Learning by Alexis Perrier

Key FeaturesCreate great machine learning models that combine the power of algorithms with interactive tools without worrying about the underlying complexityLearn the Whats next? of machine learning—machine learning on the cloud—with this unique guideCreate web services that allow you to perform affordable and fast machine learning on the cloudBook DescriptionPredictive analytics is a complex domain requiring coding skills, an understanding of the mathematical concepts underpinning machine learning algorithms, and the ability to create compelling data visualizations. Following AWS simplifying Machine learning, this book will help you bring predictive analytics projects to fruition in three easy steps: data preparation, model tuning, and model selection.This book will introduce you to the Amazon Machine Learning platform and will implement core data science concepts such as classification, regression, regularization, overfitting, model selection, and evaluation. Furthermore, you will learn to leverage the Amazon Web Service (AWS) ecosystem for extended access to data sources, implement realtime predictions, and run Amazon Machine Learning projects via the command line and the Python SDK.Towards the end of the book, you will also learn how to apply these services to other problems, such as text mining, and to more complex datasets.What you will learnLearn how to use the Amazon Machine Learning service from scratch for predictive analyticsGain hands-on experience of key Data Science conceptsSolve classic regression and classification problemsRun projects programmatically via the command line and the Python SDKLeverage the Amazon Web Service ecosystem to access extended data sourcesImplement streaming and advanced projectsAbout the AuthorAlexis Perrier is a data scientist at Docent Health, a Boston-based startup. He works with Machine Learning and Natural Language Processing to improve patient experience in healthcare. Fascinated by the power of stochastic algorithms, he is actively involved in the data science community as an instructor, blogger, and presenter. He holds a Ph.D. in Signal Processing from Telecom ParisTech and resides in Boston, MA.You can get in touch with him on twitter @alexip and by email at alexis.perrier@gmail.com.Table of ContentsIntroduction to Machine Learning and Predictive AnalyticsMachine Learning Definitions and ConceptsOverview of an Amazon Machine Learning WorkflowLoading and Preparing the DatasetModel CreationPredictions and PerformancesCommand Line and SDKCreating Datasources from RedshiftBuilding a Streaming Data Analysis Pipeline