N Jhansi mahalakshmi

Python Full Stack Intern

Dhee Coding Lab

6 mos · Bangalore Urban, Karnataka, India

As a Python Full Stack Intern, I am gaining hands-on experience in developing and deploying end-to-end web applications by integrating both frontend and backend technologies. I work with Python, Django, HTML, CSS, and React to build scalable and user-friendly solutions, while also applying my background in data analysis to enhance functionality and performance. 🔹 Key responsibilities: • Developing backend logic and APIs using Python and Django • Designing responsive user interfaces using HTML, CSS, and React • Working with databases and writing SQL queries for data management This role is helping me strengthen my problem-solving skills, understand real-world development workflows, and build impactful, data-driven applications. Leveraging prior experience in machine learning and data analysis to build intelligent, data-driven applications.

Machine Learning Engineer

InternPe

2 mos · Mangaluru, Karnataka, India

During my internship at InternPe, I worked on multiple end-to-end machine learning projects across diverse domains, applying data science techniques to solve real-world problems. My role involved data preprocessing, feature engineering, model selection, and performance optimization. Key projects included: Breast Cancer Detection – Applied Random Forest for feature selection and KNN for classification, achieving 92% accuracy in predicting cancer diagnosis. IPL Win Prediction – Built a Neural Network model to predict IPL match outcomes using features like team stats, overs, and run rates. Car Price Prediction – Implemented Linear Regression to estimate car prices based on make, company, and fuel type, emphasizing regression modeling and evaluation. Diabetes Prediction System – Developed a predictive model using Random Forest Classifier, achieving 73.8% accuracy and visualizing health insights through interactive plots. Skills applied: Python, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Keras, Neural Networks, Feature Engineering, Data Visualization, Model Evaluation, and Problem Solving. This internship strengthened my ability to design and deploy scalable ML systems, perform exploratory data analysis, and translate analytical findings into actionable insights.

Machine Learning Intern

Internpe

Jan 2024 – Apr 2024

Designed and deployed machine learning models across healthcare, sports analytics, and pricing domains using Python, Scikit-learn, and Keras. Applied classification, regression, feature selection, and neural networks. Delivered models including Breast Cancer Detection with 92% accuracy, Diabetes Prediction with 73.8% accuracy, IPL match outcome prediction, and Car Price Estimation.

Python Full Stack Intern

DCL

Undergoing structured training in Python full stack development, including Python, SQL, HTML, and CSS. Learning backend fundamentals, database connectivity, SQL queries, responsive web page development, and full-stack architecture.