Best Selling Books by Sarah Guido

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You''ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas M?ller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you''ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills.

Vous aussi participez à la révolution qui ramène l''intelligence artificielle au coeur de notre société, grace aux data scientists. La data science consiste à traduire des problèmes de toute autre nature, en problèmes de modélisation quantitative, résolus par des algorithmes de traitement. Ce livre se présente comme une référence pour tous les développeurs, statisticiens ou chefs de projets ayant à résoudre des problèmes liés à la data science. Au programme : Pourquoi utiliser le machine learning Les différentes versions de Python L''apprentissage non supervisé et le préprocessing Représenter les données Processus de validation Algorithmes, chaînes et pipeline Travailler avec des données de type texte Du prototype à la production

"Python is quickly becoming the go-to language for data analysis, but it can be difficult to figure out which tools to use. In this webcast you''ll get a bird''s eye overview of some of the best tools for data analysis and how you can apply them to your workflow. She''ll introduce you to how you can use Pandas, Scikit-Learn, NLTK, MRJob, and matplotlib for data analysis."--Resource description page.