Hi, I'm Shashank R 👋

Completed Three project-based internships focused on building end-to-end machine learning solutions.

Customer Churn Prediction (Telecom):
Executed the full ML pipeline including data cleaning, preprocessing, feature engineering, EDA, model development, and evaluation. Achieved strong results using precision, recall, F1-score, and ROC-AUC, and delivered business insights to support churn-reduction strategies.

Sentiment Analysis (NLP):
Executed the complete NLP pipeline including text cleaning, preprocessing, tokenization, stop-word removal, and lemmatization. Built and evaluated a sentiment classification model using TF-IDF, SMOTE, and Linear SVM, achieving strong performance metrics. Generated actionable sentiment insights to support customer experience improvement and product feedback analysis.

Customer Segmentation:
Developed a customer segmentation model using clustering algorithms such as K-Means and hierarchical clustering to group customers based on purchasing behavior and demographic patterns. Performed data preprocessing, feature scaling, and exploratory data analysis (EDA) to identify meaningful patterns in customer data..

Gained strong practical experience in ML workflows, analytical thinking, and transforming raw data into actionable insights.

Completed an intensive, industry-oriented training program in Data Science and Machine Learning with hands-on implementation.

Technical Areas Covered:
Python, Pandas, NumPy, Matplotlib, Seaborn, SQL, Statistics, EDA, Data Preprocessing, Feature Engineering, and Machine Learning algorithms (Regression, Classification, Clustering).

ML Deployment:
Applied model evaluation techniques and deployed ML solutions using Streamlit.

Developed multiple end-to-end capstone projects including Telecom Analytics, Recommendation Systems, and Predictive Modeling, demonstrating real-world problem-solving and strong ML foundations.