I presented a 15-minute lightning talk on leveraging AutoML for sentiment analysis.
Quick and easy AutoML for Sentiment Analysis and Classification tasks
“Machine learning algorithms have evolved significantly in the last few years. AutoML is one of the latest advancements in the field that allows anyone to build and deploy AI products without requiring extensive knowledge in the field. The lightning talk will show case how one can build a production-quality sentiment analysis model using Google AutoML and Google Cloud with the least coding possible.”
I first showed case how to upload datasets directly into Google AutoML NLP portal and, from there, train a model and perform predictions. After that, I showed how I integrated the sentiment analysis model into analyzing Twitter stream using Django, Docker, Twitter API/Tweepy, Jupyter Notebooks, and PostGresQL, I published the code on GitHub under hoteit/courses-sentiment-tweets