Applied Text Analysis Book Release Party

Interested in integrating natural language processing into your applications? Want to learn how to build language-aware data products? Like free O’Reilly books??

Come to celebrate the release of Applied Text Analysis with Python with authors Benjamin Bengfort, Rebecca Bilbro, and Tony Ojeda. ( http://shop.oreilly.com/product/0636920052555.do ) This new O’Reilly title presents a data scientist’s approach to building language-aware products with applied machine learning. The authors will be signing copies of their book and hors-d'oeuvres will be served.

About Applied Text Analysis with Python:
From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. Readers will learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering.

About the Authors:
Benjamin Bengfort is a data scientist who lives inside the Beltway but ignores politics (the normal business of DC) favoring technology instead. He is currently working to finish his Ph.D. at the University of Maryland where he studies machine learning and distributed computing. His lab does have robots (though this field of study is not one he favors) and, much to his chagrin, they seem to constantly arm said robots with knives and tools; presumably to pursue culinary accolades. A professional programmer by trade, a Data Scientist by vocation, Benjamin’s writing pursues a diverse range of subjects from Natural Language Processing, to Data Science with Python to analytics with Hadoop and Spark.

Dr. Rebecca Bilbro is a data scientist, Python programmer, teacher, speaker, and author in Washington, DC. She specializes in visual diagnostics for machine learning, from feature analysis to model selection and hyperparameter tuning, and has conducted research on natural language processing, semantic network extraction, entity resolution, and high dimensional information. An active contributor to the open source software community, Rebecca enjoys collaborating with other developers on inclusive, high-impact projects like Yellowbrick—a pure Python package that aims to take predictive modeling out of the black box. Rebecca earned her doctorate from the University of Illinois, Urbana-Champaign, where her research centered on communication and visualization practices in engineering.

Tony Ojeda is a data scientist, author, and entrepreneur with expertise in business process optimization and over a decade of experience creating and implementing innovative data products and solutions. He is the founder of District Data Labs, a data science consulting and corporate training firm, research lab, and open source collaborative where people from diverse backgrounds come together to work on interesting projects. He also co-founded Data Community DC. Tony has a Masters in Finance from Florida International University and an MBA with concentrations in Strategy and Entrepreneurship from DePaul University in Chicago.

The parking garage is for a few buildings, follow the green columns. If you don't see any parking on the first level, drive just past the exit on the first level, and make a sharp left turn to access "Additional Parking" down the ramp. Proceed down the ramp, make 2 left turns and you'll see additional green columns.