Kevin Freire
About Kevin Freire
Kevin Freire is a Data Science Fellow at SharpestMinds in Toronto, Canada, with a background in Electrical Engineering and Artificial Intelligence from Ryerson University. He has developed various text classification and name-entity-recognition models, and has experience in web scraping and data pre-processing.
Work at SharpestMinds
Kevin Freire has been serving as a Data Science Fellow at SharpestMinds since 2022. In this role, he applies his expertise in data science to various projects, focusing on developing models and algorithms that enhance data analysis capabilities. His work contributes to the organization's mission of providing mentorship and support to aspiring data scientists.
Education and Expertise
Kevin Freire holds a Bachelor of Engineering (B.Eng.) in Electrical Engineering from Ryerson University, which he completed from 2013 to 2018. He further advanced his education by obtaining a Master of Engineering (M.Eng.) in Artificial Intelligence from the same institution, graduating in 2022. His academic background equips him with a strong foundation in engineering principles and advanced data science techniques.
Background in Data Science
Kevin has developed a full-stack web application for text classification, which is deployed on the cloud. This application enables users to classify text as negative, positive, or neutral. He has implemented various models, including a text classification model using Scikit-Learn, achieving a 70% accuracy rate, and a Name-Entity-Recognition model utilizing a pre-trained Spacy model.
Previous Work Experience
Prior to his current roles, Kevin worked as a Meter Technician at Impark from 2017 to 2018. He has also been employed at Lumen Technologies as Network Operations II since 2019. In these positions, he has gained practical experience in technical operations and data processing, further enhancing his skill set in the field of data science.
Technical Projects and Skills
Kevin has developed a web scraping algorithm using BeautifulSoup4 to extract content from news articles for Name-Entity-Recognition tasks. He has also created a data pre-processing pipeline using NLTK and trained a TF-IDF model for feature engineering in text classification projects. These technical skills demonstrate his ability to handle complex data tasks effectively.