FIRAS TLILI

Machine Learning Engineer

Intelligent Machines Laboratory •  January 2020 - December 2022

• Successfully trained a custom deep learning model using YOLOv7 to detect soccer highlights. • Created a Python script that effectively extracted highlights from videos. • Developed a Django Web Application to deploy the model and build a user-friendly interface for easy access using HTML , CSS , JavaScript and Bootstrap . • Optimized the deep learning model to improve its accuracy to acheive 90 %. • Collaborated with a team to ensure the project was completed on time and within budget. • Conducted extensive testing and debugging to ensure the model was functioning correctly. • Implemented user feedback to improve the interface and functionality of the application. • Documented the project thoroughly, including technical specifications and user manuals, for future reference.

Software Engineer

Freelancer•  January 2014 - December 2019

• Successfully developed and deployed a real-time data analysis tool using Python that enabled the company to identify potential revenue opportunities and improve its profitability by 20%. • Designed and implemented a web scraping system using Python, which enabled the company to efficiently gather and analyze data from various sources, resulting in increased productivity and accuracy of data analysis. • Mentored junior Python developers, resulting in improved code quality and productivity across the team • Developed and deployed a binary classifier using Azure Machine Learning to predict whether a patient should be tested for diabetes based on medical data, using logistic regression to train the model and an Azure Container Instance to deploy it as a web service (October 2022) • Developed a machine learning model to classify financial news articles into categories, using decision tree algorithm to train the model (September 2022) • Developed and deployed a model using Azure Machine Learning to predict the price of a car based on its features data, using linear regression to train the model and an Azure Container Instance to deploy it as a web service (August 2021) • Successfully developed and deployed a real-time data analysis tool using Python that enabled the company to identify potential revenue opportunities and improve its profitability by 20%. • Designed and implemented a web scraping system using Python, which enabled the company to efficiently gather and analyze data from various sources, resulting in increased productivity and accuracy of data analysis. • Mentored junior Python developers, resulting in improved code quality and productivity across the team • Developed and deployed a binary classifier using Azure Machine Learning to predict whether a patient should be tested for diabetes based on medical data, using logistic regression to train the model and an Azure Container Instance to deploy it as a web service (October 2022) • Developed a machine learning model to classify financial news articles into categories, using decision tree algorithm to train the model (September 2022) • Developed and deployed a model using Azure Machine Learning to predict the price of a car based on its features data, using linear regression to train the model and an Azure Container Instance to deploy it as a web service (August 2021)