Focus : Python, R, and SQL are my go-to tools, and I'm always eager to learn more.
Specifications : Ms Excel, SQL, Python, Power BI,R
Languages
English, Hindi, Kannada,Hobbies
Travelling, Participating in Cultural Fests and Festivals
Summary
Hello, I am a Data Science graduate student with hands-on experience in machine learning and predictive modeling. Proficient in Python, SQL, and R, with a strong foundation in statistical analysis and data preprocessing. Demonstrated ability to develop and implement ML models for real-world applications, including customer churn prediction, spam detection, and fraud detection. Multilingual professional with excellent communication skills and a quick adaptability to new technologies. Seeking opportunities to leverage technical expertise and analytical skills in a challenging data science role.
Education History
Internships
During my time at Encryptix, I worked on three impactful machine learning projects:
• Customer Churn Prediction using Logistic Regression: - I developed a model to predict customer churn by leveraging logistic regression. - This involved processing customer demographics and usage data to achieve high accuracy in identifying at-risk customers. - Key insights included factors like tenure, credit score, and estimated salary.
• Spam SMS Detection using Naive Bayes Multinomial NB: - I built a spam detection model using the Naive Bayes Multinomial NB algorithm. - By converting SMS text data into numerical format with TF-IDF, I achieved reliable spam detection. - The model effectively identified spam messages based on specific keywords and phrases.
• Credit Card Fraud Detection using Random Forest Classifier: - I created a fraud detection model using the Random Forest Classifier. - The result was a robust model that achieved high accuracy in detecting fraudulent transactions.
• These projects provided me with hands-on experience in data preprocessing, model building, and evaluation, enhancing my skills in machine learning and data science.