Denim Giri

Motivated software intern with hands-on experience in coding, debugging, and testing applications. Possess strong problem-solving skills and the ability to work well in teams. Demonstrated success in improving application functionality through innovative design and optimization strategies. Eager to leverage this background into a progressive role in software development.

PYTHON & DJANO PROFESSIONAL TRAINING | Mar 17 – May 2, 2024

● Successfully completed a backend development training program in Python and Django, created messaging & audio call applications, along with a blog web application

● Gained hands-on experience in developing RESTfulAPIs, managing databases, and integrating third-party services using Django

DATA SCIENCE WITH PYTHON | Dec 3 – Mar 3, 2023

● Developed a machine learning model to classify flowers’ species based on key characteristics, utilizing Scikit-learn for model building & hyperparameter tuning.

● Utilized Pandas , NumPy ,Scikit-learn,and Complex Statistical Model for creating organized data frame for processing, visualized data and model performance using Matplotlib, identifying patterns and feature selection

OBJECT-ORIENTED PROGRAMMING WITH JAVA |Jan 2025

• Completed training focused on core concepts of object-oriented programming, emphasizing Java syntax and practical application.

DATA STRUCTURES & ALGORITHMS WITH PYTHON | Jan 2025

• Completed certification focused on mastering core data structures and algorithm concepts, with hands-on coding exercises in Python.

AI-Enhanced Blogging Platform | Python, Django, MySQL, OpenAI API

• Developed a full-stack web application allowing users to register, manage profiles, and create and publish blogs.
• Integrated MySQL for efficient database management, storing user profiles, posts, and related metadata.
• Leveraged OpenAI's API to automatically assign relevant tags to blog posts, enhancing user experience and content discoverability.
• Implemented RESTful APIs for seamless frontend-backend interactions.

Machine Learning Flower Classifier | Python, Pandas, NumPy, Matplotlib, Scikit-learn, Seaborn, TensorFlow, SciPy

• Engineered and deployed a robust supervised machine learning model achieving high accuracy in classifying flower species based on detailed petal and sepal morphological characteristics.
• Executed comprehensive data preprocessing, normalization, feature scaling, and dimensionality reduction using Pandas, NumPy, and SciPy, significantly enhancing dataset quality and predictive performance.
• Applied advanced statistical techniques including correlation analysis, PCA (Principal Component Analysis), and hyperparameter tuning through grid search to optimize model performance.
• Conducted exploratory data analysis with visualization libraries Matplotlib and Seaborn to reveal patterns, identify critical features, and evaluate model effectiveness.
• Integrated TensorFlow for exploring and implementing neural network-based classification models, expanding the project scope and predictive capabilities.

Reddit Soccer Post Classification | Python, NLP, NLTK, Pandas, Scikit-learn

• Developed a natural language processing model to classify Reddit posts related to soccer matches based on categories such as team performance, fan sentiment, and injury reports.
• Utilized NLTK for text tokenization, sentiment analysis, and keyword extraction, enhancing the accuracy of topic categorization.
• Leveraged Pandas for structured data handling and Scikit-learn for training and evaluating machine learning classification models, ensuring accurate and consistent categorization of posts.

AI-Powered Weather Forecasting | Python, Scikit-learn, OpenAI API, Pandas, NumPy, React, Django

• Developed a complete web-based weather forecasting application using React for frontend interaction and Django for backend services.
• Implemented predictive machine learning models using Scikit-learn to forecast weather conditions based on historical climate data.
• Integrated OpenAI API to provide dynamic and personalized activity recommendations tailored to predicted weather conditions, significantly enhancing user interaction and experience.
• Employed Pandas and NumPy for robust data processing and analysis, ensuring precise forecasting and actionable insights.