SHOUVIK GHOSH

I am a dedicated electrical engineering graduate with a B.Tech and a diploma in the field. I have a solid technical foundation, including knowledge of Python, ML, and cloud computing technologies. My experience as a Cloud Engineer trainee has equipped me with valuable industry insights. I am passionate about automation (AI) projects and have demonstrated leadership in team-based assignments. I thrive in collaborative environments and am committed to continuous learning.

• Home Automation Project

Projects focused on home automation using Arduino sketches and code writing led to the Voice Control Home Automation project, while credit card fraud detection using machine learning in Python developed a model to detect fraudulent transactions in imbalanced data, ensuring quick classification and user privacy

• Credit card fraud detection using machine learning in Python

Imbalanced data, i.e., most of the transactions (99.8%) are not fraudulent, which makes it hard to detect the fraudulent ones

1. The model must be simple, and fast enough to detect the anomaly and classify it as a fraudulent transaction as quickly as possible

2. Imbalance can be dealt with by properly using some methods, which we will discuss in the next paragraph

3. The data's dimensionality can be reduced to protect the users' privacy

PwC Switzerland Power BI Job Simulation on Forage, Demonstrated expertise in data visualisation through the creation of Power BI dashboards that effectively conveyed KPIs.