Data Science with Artificial Intelligence Intern
Currently pursuing an internship at Labmentix, where I am actively involved in end-to-end machine learning project development. My work follows a complete ML lifecycle:
1️⃣ Problem Definition: Understanding project goals and defining success metrics for business-focused AI solutions.
2️⃣ Data Collection: Working with structured/unstructured data from APIs and internal sources.
3️⃣ Exploratory Data Analysis (EDA): Using Matplotlib and Seaborn to identify trends, clean data, and handle missing values.
4️⃣ Data Preprocessing: Encoding, normalization, and feature engineering for model readiness.
5️⃣ Model Building: Creating classification models like Logistic Regression, Decision Trees, Random Forest, and Boosting using Scikit-learn.
6️⃣ Model Evaluation: Using metrics such as accuracy, F1-score, and confusion matrix to validate model performance.
7️⃣ Deployment (Upcoming): Planning model deployment using Flask and exploring integration with cloud services.
Gaining hands-on experience in solving real-world problems through data-driven insights and intelligent automation.
