Data Science Machine-Learning Natural Language Processing Open-Source Use CaseSee in schedule
In this workshop, through hands on coding exercises, participants will learn how to use an open source chatbot framework, RASA, in conjunction with an NLP library, NLTK, to build a chatbot that gathers customer feedback and generates a report regarding the sentiment of the text.
In the first part, we will introduce RASA, including how to build and train a chatbot using RASA. We will start from scratch, covering the necessary installation steps, then setting up the project, and building a simple working chatbot. These steps will include setting up a pipeline for the RASA NLU, learning how to write a training file for the NLU intent, using the custom form action to get and handle users’ feedback, and writing the stories that make up the dialogue flow.
In the second part, we will cover the sentiment analysis tool NLTK. This will enable a deeper use of RASA, including more custom settings in the architecture. We will explain how sentiment analysis in NLTK works and integrate that sentiment analysis in the chatbot so that it can handle users differently according to their expressed sentiment. We will create a custom action that handles the sentiment analysis and stores the result, a measure of the positivity or negativity of the user dialogue that can be used to generate reports, or prompt different responses, etc.
This workshop is for people who are confident programming in Python and who have a basic understanding of NLP.
Update: slides at https://slides.com/cheukting_ho/rasa_chatbot_workshop
Type: Training (180 mins); Python level: Intermediate; Domain level: Intermediate
After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk has been a Data Scientist in one of the biggest worldwide wholesaler in travel business and Inawisdom, an AWS partnered consultancy which deliver machine learning model.
Cheuk constantly contributes to the community by giving AI and deep learning workshops, organize sprints for open source projects, volunteering at Datakind for charities. At the same time contribute to open source projects including Pandas, Keras, Scikit-learn and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData in Amsterdam and Berlin, PyCon in Israel, UK and Germany, EuroPython and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion.
Kara is CloudBees Open Source Community Manager. Previously, Kara worked as a web developer for a Fortune 500 company, as a freelancer, and for charities. Kara is a proponent of open source and has contributed to Pandas, Babel, and Jaeger, amongst others. As an organiser and board director of codebar.io, Kara works to increase diversity in the tech industry.