About This Book, Leverage Python' s most powerful open-source libraries for deep learning, data wrangling, and data visualization, Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms, Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets, Who This Book Is For, If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource., What You Will Learn, Explore how to use different machine learning models to ask different questions of your data, Learn how to build neural networks using Keras and Theano, Find out how to write clean and elegant Python code that will optimize the strength of your algorithms, Discover how to embed your machine learning model in a web application for increased accessibility, Predict continuous target outcomes using regression analysis, Uncover hidden patterns and structures in data with clustering, Organize data using effective pre-processing techniques, Get to grips with sentiment analysis to delve deeper into textual and social media data, Style and approach, Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
