Data science student with a solid background in data analytics and machine learning. Familiar with industry-standard methodologies and adept at tackling real-world challenges. Capable of extracting insights from data to inform decision-making. Strong analytical skills complemented by a focus on practical applications.
• Developing a image classification project for diabetic retinopathy using transfer learning techniques. Conducted data preprocessing through resizing, normalization, and augmentation methods.
• Optimized pre-trained networks via fine-tuning to enhance model performance. Assessed model using key metrics such as accuracy, precision, recall, F1-score, and AUC.
• Developed expertise in data analytics and machine learning, focusing on data-driven decisions.
• Engaged with real-world datasets to familiarize with key industry tools and methodologies. Refined problem-solving skills through direct experience in diverse analytical contexts.
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