Proactive Data Scientist & Data Analyst with 3+ years of experience in SQL, Machine Learning, Natural Language Processing, and Python. Seeking a challenging role to leverage analytical and problem-solving abilities. Proven track record delivering accurate insights and developing large-scale web applications with Flask and Streamlit. Effective driver of the data science lifecycle from data collection to actionable insights. Communicative and collaborative with a history of improving data-driven operations to support corporate goals and enhance decision-making processes.
PROJECT 1 - Financial Sentiment Analysis, The goal is to develop a machine learning model for financial sentiment analysis to gauge the impact of financial statements on business and government. And also, to classify the sentiment of financial statements as positive, negative, or neutral, and use this information to make informed business decision and government policies.
PROJECT 2 - Electric Motor Speed Prediction, The goal is to predict motor speed based on the other attributes available in the dataset. This includes sensor Data such as ambient temperature, coolant temperature, voltage and current components, torque and temperature Measurements of various parts of the motor. The goal is likely to improve performance and efficiency of the Permanent magnet synchronous motor (PMSM) by understanding the relationship between the sensor data and motor speed.
PROJECT 3 - Credit Card Default Prediction, The goal is to predict the probability of credit default based on credit card owner's characteristics and payment history.
PROJECT 4 - Rock Paper Scissors Prediction, This Rock, Paper, Scissors game utilizes machine learning with a Keras and Tensor Flow-powered neural network. By analyzing a dataset of user interactions, the model predicts moves, offering a modern and adaptive gaming experience. Experience the classic game with a cutting-edge twist!
PROJECT 5 - Object Detection, Live Tracking and Segmentation using YoloV8 (Computer Vision), The goal is to implement and optimize an intelligent vehicle transport system using YOLOv8 Ultralytics, incorporating Object Detection, Segmentation, and Tracking. The primary goal is to enhance real-time monitoring, improve safety measures, and contribute to the evolution of efficient and innovative solutions within the realm of smart transportation.