M.Sc. Physics | Aspiring Data Scientist | Data Analyst
Holder of a Science degree from the University of Calcutta, I furthered my academic journey with a Master's in Physics, specializing in Solid State Physics from Osmania University, Hyderabad. Driven by a passion for data, I am actively pursuing a career as an aspiring data scientist and data analyst, aiming to leverage my academic foundation in physics to bring a unique perspective to the world of data.
Greetings, I'm Ritabrata Chakraborty, an individual with a profound background in physics who has transitioned into the dynamic realm of data science. My academic journey includes the attainment of a Master's degree in Physics, where I delved into the intricacies of understanding the universe.
Presently, my focus is keenly directed towards the expansive field of data science. I am actively immersing myself in the intricacies of machine learning and deep learning. Proficient in the Python programming language, I harness my skills across a spectrum of tools and frameworks, including scikit-learn, numpy, pandas, and matplotlib. This enables me to adeptly navigate and tackle complex challenges within the realm of data. Furthermore, I bring valuable experience in data analytics, demonstrating expertise in SQL, spreadsheet applications, and Tableau.
I have demonstrated my commitment to continuous learning by obtaining certifications in Data Science from platforms such as Coursera. Notably, I have successfully completed the Machine Learning Specialization, Deep Learning Specialization, Mathematics for Data Science and Machine Learning Specialization, showcasing my dedication to acquiring versatile skills in this dynamic field. Furthermore, I have recently completed the Data Analytics program offered by Google, further expanding my expertise in the field.
Apart from my professional pursuits, I find joy in hiking and trekking, seamlessly blending them with my passion for photography. In addition, I take pleasure in both watching and playing football as part of my recreational activities.
Developed a flight fare prediction model using a Random Forest Regressor algorithm, trained on historical flight data, and implemented a user-friendly web application for fare predictions. Utilized data preprocessing, feature engineering, and hyperparameter tuning for model optimization.
Developed a flight fare prediction model using a Random Forest Regressor algorithm, trained on historical flight data, and implemented a user-friendly web application for fare predictions. Utilized data preprocessing, feature engineering, and hyperparameter tuning for model optimization.
This project contains the exploratory data analysis and model training of a student performance indicator dataset. The data cleaning, analysis and visualization has been done on Jupyter Notebook. The visualization has also been done on tableau.
New projects will be uploaded soon.
New projects will be uploaded soon.
New projects will be uploaded soon.
