This consulting project at Insight is to build a question classifier for scalable genetic test chatbot.
The user input can be in free style. The question classifier is essential to understand the intent of user input and to retrieve information from database.
With the help of state-of-art models, Long Short Term Memory (LSTM) and Global Vectors (GloVe), high classification accuracy is achieved in the project.
The slides and demo are shown below.
Feel free to contact me for further questions!
Shujian Liu is currently a Data Science Fellow at Insight Data and PhD candidate at UMass Amherst. At Insight, he finished a consulting project helping the company build a question classifier for scalable genetic test chatbot. In his doctoral research, he applied machine learning and high performance computing to offshore floating wind turbine.
He has been a computational mathematical researcher with 7+ years' experience in scientific software development. He has solid theoretical knowledge of machine learning, data mining and natural language processing. He is skilled in mathematical algorithms and high performance computing (CUDA/OpenMP). He has great passion for software development and data science.