Mohammed Tauheed Shariff

Recent MSc Data Science graduate with a UK Graduate Visa, specializing in Machine Learning, NLP, and Data Analytics. Proficient in Python, R, SQL, and AWS. Experienced in predictive modeling, statistical analysis, and business intelligence. Applied skills in real estate, healthcare, and e-commerce industries. Demonstrated ability to analyze complex datasets, develop accurate ML models, and provide actionable insights. Passionate about leveraging data and AI to tackle real-world challenges and drive business impact.

Social Media Sentiment Analysis of the Israel-Palestine Conflict (MSc Dissertation)

(06/2024 - 10/2024)

• Analyzed 1.8M Reddit comments using NLP (VADER, LDA, NRC Emotion Lexicon), classifying 45% as negative, 30% as neutral, and 25% as positive.
• Identified 6.5% misinformation and forecasted sentiment trends using Facebook Prophet.
• Provided insights into public opinion trends and misinformation patterns, aiding better understanding of online discourse.

Predictive Modeling for Breast Tumor Classification

(11/2023 - 02/2024)

• Developed a machine learning model to classify breast tumors as malignant or benign, improving early detection rates with 98.24% accuracy.
• Conducted feature engineering using 10 key tumor characteristics, achieving a recall score of 89.66%.
• Implemented deep learning techniques to enhance model performance and classification accuracy.

Real-Time Object Detection System Using YOLOv5

(07/2024 - 09/2024)

• Developed an AI-powered system to detect and classify objects in real-time, improving automation and security applications.
• Enhanced model accuracy through data processing, image augmentation, and fine-tuning parameters.
• Designed a user-friendly web interface using Flask, allowing real-time interaction with the detection system.