Vedant Bansod

I am a motivated and technically proficient AI engineer with a strong foundation in machine learning, deep learning, and data preprocessing. My expertise lies in utilizing Python, Pandas, NumPy, and various ML frameworks such as scikit-learn, TensorFlow, and Keras. I have a solid understanding of supervised and unsupervised learning, feature engineering, and model evaluation techniques. My passion for applying AI to solve real-world problems drives my commitment to continuous learning and improvement.

Throughout my academic journey, I have successfully completed several projects that showcase my skills and dedication. Notably, I trained a Convolutional Neural Network (CNN) on the MNIST dataset, achieving an impressive 99% test accuracy using Keras and TensorFlow. Additionally, I built a spam email classifier using the Naïve Bayes algorithm and TF-IDF, reaching 95% precision. My participation in Kaggle competitions has further honed my skills, where I ranked in the top 20% for a tabular prediction challenge.

One of my significant projects includes developing a real-time face mask detection system using CNNs and OpenCV, which achieved 95% accuracy. I also created an AI-powered resume parser that extracts structured information from unstructured resume PDFs, achieving 93% extraction accuracy using Named Entity Recognition (NER) and Transformer-based techniques. I am eager to leverage my skills and knowledge in a challenging role that allows me to contribute to innovative AI solutions.