StackUp Webinar: Text Processing 101 using the spaCy library

Text data is one of the most common forms of “unstructured” data. Unstructured data does not fit neatly into traditional databases, because they can be any length. For example, this paragraph you are reading contains more words than the title. How do you start parsing and processing this type of data, beyond doing traditional string-based searching, regular expressions, or word-for-word matching?

SpaCy is a popular Python natural language processing library that gets you started with text processing very quickly. It is both flexible and powerful, and comes packaged with word vectors, named-entity recognition, and other features.

In this webinar, you see how to take any blob of text data, tokenise it, and extract information such as keywords using spaCy on Google Colaboratory. You also get some time to play around with spaCy and try your own text data.

Note: This is a demo-oriented workshop to teach you the basic concepts. We assume that you have a working knowledge with at least one programming language.

Anyone new to text processing

Pre-requisite:
Knowledge of Python or another programming language.

26 June 2020,Friday
2.00 pm - 4:00 pm (You may start logging in from 1.30pm)
The session will be conducted using a webinar format. Details and link for the webinar will be sent to participants closer to the date.

Free webinar Register Now

Speaker

Ms. Lisa Ong

Principal Lecturer and Consultant, Software Systems Practice , NUS-ISS
View Biography

Lisa is with the Software Engineering and Design Practice, StackUp program for National University of Singapore, Institute of Systems Science (NUS-ISS).

Lisa has multiple years of extensive experience in software product research and development at Microsoft Corporation (USA). Her background includes writing and delivering operating systems code, building and deploying web services, and also building AI systems in recent years.

At Microsoft, Lisa has led and participated in many interesting projects including the Microsoft Embedded Learning Library, involved compressing and deploying computer vision and machine learning algorithms on tiny devices. While part of the Windows product team, Lisa delivered operating system features such as a unified sensors API and driver stack, the Media Transfer Protocol stack, and geo-fencing capabilities on Windows OneCore.

Before Microsoft, Lisa had a stint at Nuance Communications (USA) as an Embedded Software Engineer, working on small footprint text to speech systems.

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