As a machine learning engineer with 3+ years of experience in the field, I have a broad range of capabilities that could be valuable to your organization. My expertise lies in several areas of artificial intelligence, including machine learning, deep learning, computer vision, and data science. I have a track record of developing and implementing AI solutions that help organizations to improve their operations, increase efficiency, and achieve their goals.
In my previous roles, I have worked on research projects, and deep learning internships, and contributed to AI-for-good projects, where I have developed a variety of skills, including algorithm development, data analysis, computer vision, and model deployment.
I have worked on several projects that demonstrate my capabilities, including Super-Resolution of an Image using GAN, Instance Segmentation on crack data using Mask R-CNN, Background Subtraction, Content-based Image Retrieval, analysis, and time-series based forecasting on the Birmingham car parking dataset, car detection using YOLO, and implementing the GRAD-CAM with sanity checks (unofficial implementation of ‘Sanity Checks for Saliency Maps’ NIPS - 2018).
In addition to my technical skills, I am highly motivated to use AI for social good and have participated in several AI-for-good projects like the Fighting Illegal Dumping Challenge with Omdena, where I collaborated with 50 other AI practitioners to develop models for identifying sustainable and environmental friendly products and recycling bins using deep learning and computer vision techniques.
Overall, my capabilities as a machine learning engineer include developing and implementing AI solutions, data analysis, computer vision, and algorithm development. I am highly motivated, have a strong work ethic, and am always eager to learn new skills and technologies to stay on top of the latest trends in AI.