Natural Language Processing: Sentiment Analysis of Customer Reviews using transformers (BERT)
About This Video
“During the workshop, I will illustrate how pre-trained models can be utilized for sentiment analysis to evaluate customer reviews data. The session will begin with a brief overview of the theory behind working transformers (which is the base of BERT & GPT models), including explanations of concepts such as zero-short training, few short training, and fine-tuning. Following this, I will provide a code walk through for the end-to-end implementation of the BERT classification model for sentiment analysis. The workshop will consist of a 15-20 minute presentation approximately, followed by a detailed code walk through.”
In This Video
Student, Northeastern University
Rutuja is currently in the final semester of her Master of Science degree in Data Analytics with a specialization in Machine Learning from Northeastern University. Prior to her academic pursuits, she worked as a Data Scientist at Larsen & Toubro Infotech. During her research assistantship at Northeastern University, she focused on Natural Language Processing Models and Recommendation Systems, gaining extensive experience in these areas. At Larsen & Toubro Infotech, she worked with Citibank clients on credit risk analysis and customer segmentation. With her previous internships and work experience, she has honed her skills in solving business problems in the Retail and Finance industries. A fun fact about Rutuja is that in 2019 she accomplished a remarkable feat by completing a 100-mile cycling ride