Machine Learning with Text in scikit-learn (PyData DC 2016)

Although numeric data is easy to work with in Python, most knowledge created by humans is actually raw, unstructured text. By learning how to transform text into data that is usable by machine learning models, you drastically increase the amount of data that your models can learn from. In this tutorial, we'll build and evaluate predictive models from real-world text using scikit-learn. (Presented at PyData DC on October 7, 2016.) GitHub repository: https://github.com/justmarkham/pydata-dc-2016-tutorial Enroll in my online course: http://www.dataschool.io/learn/ Subscribe to the Data School newsletter: http://www.dataschool.io/subscribe/ == OTHER RESOURCES == My scikit-learn video series: https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A My pandas video series: https://www.youtube.com/playlist?list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y == JOIN THE DATA SCHOOL COMMUNITY == Blog: https://www.dataschool.io Twitter: https://twitter.com/justmarkham Facebook: https://www.facebook.com/DataScienceSchool/ YouTube: https://www.youtube.com/user/dataschool?sub_confirmation=1 Join "Data School Insiders" to receive exclusive rewards! https://www.patreon.com/dataschool