I'm a B. Tech student majoring in Artificial Intelligence and Machine Learning, deeply passionate about data science's transformative potential. With a strong foundation in Python, R, and machine learning frameworks, I aspire to contribute to innovative projects that drive meaningful change. Dedicated to achieving demanding development objectives according to tight schedules while producing impeccable code.
Attended the seminer on “QUANTUM INTELLIGENCE”
Completed a focused IoT training with a hands-on project, developing a Vehicle Tracking System. Demonstrated expertise in sensor integration, wireless communication, and real-time analytics.
Natural Language Processing with Classification and Vector Spaces
The CO2 Emission Prediction project employs Support Vector Machine regression to tackle the critical challenge of forecasting carbon dioxide emissions in urban environments.
https://github.com/RitamHalder/Data_Science_ritam_1st/blob/main/Determining_CO2_Emissons.ipynb
Analyzed public sentiment on COVID-19 data using LSTM for insights into public perception and concerns. This is a NLP related project using TensorFlow's KerasNLP API. The COVID-19 Sentiment Analysis (LSTM) project is developed on a dataset which is collected from twitter. This data-driven initiative gauge public sentiments and emotional responses during the pandemic.
https://github.com/RitamHalder/Data_Science_ritam_1st/blob/main/Sentiment_analysis on Covid19.ipynb
The Tesla Stock Price Forecast project employs ARIMA modeling to predict Tesla's stock price movements. By analyzing historical stock data, this project aims to provide valuable insights for investors and traders.
https://github.com/RitamHalder/Data_Science_ritam_1st/blob/main/Time Series Analysis.ipynb
Utilizing LightGBM, this project tackles fraud detection in diverse payment categories, including debit, cash out, cash in, and transfers, using a substantial dataset comprising over 6.3 million samples. It bolsters financial security by swiftly identifying and preventing fraudulent activities in these payment channels.
https://github.com/RitamHalder/Data_Science_ritam_1st/blob/main/Fraud_detection_using_LightGBM.ipynb