KAWSAR HAMID

Aspiring AI practitioner currently pursuing a Master’s in Artificial Intelligence, with a strong foundation in software development and a passion for learning machine learning, deep learning, and generative AI. Proficient in Python and experienced in building RESTful APIs and web applications using Django. Actively developing skills in model training, data preprocessing, and AI system integration. Seeking an internship opportunity to apply academic knowledge, gain hands-on experience, and contribute to innovative AI projects.

• Vice Chancellor Award for the best Thesis at the period of undergraduate.
• Accepted by ICCIT 2022 Conference
• Published on IEEE Xplore

Prediction of Cryptocurrency price using machine learning technique and public sentiment analysis., https://ieeexplore.ieee.org/document/10055524

• Heart Disease Prediction, It was a classification problem. To predict whether a person has heart disease or not, we used Random Forest Classifier. The accuracy was good.
• Stock Price Prediction, We used LSTM (Long Short Term Memory) to predict the price of stock and the dataset was collected from Kaggle.
• House Price Prediction, Using the Random Forest Regressor machine learning algorithm through the Scikitlearn library, the house price prediction project has been done.
• Object Detection, In this project, we used an image dataset to detect the object. We used a sequential model in this project. The accuracy was more than 80 percent.
• Face Mask Detection, In this project, we used an image dataset to detect the object. We used a sequential model in this project. The accuracy was more than 80 percent.