Programming and ML
Skilled in Python with expertise in libraries like NumPy, Pandas, Scikit-learn, and TensorFlow. Proficient in deep learning and practicle implementation in regression, classification, and model optimization.
As a Data Scientiest, Data drives me. Explore my portfolio for a glimpse into my world of insightful analysis, machine learning, and predictive modeling.
Armed with a Master's in Data Science and a Bachelor's in Mechatronics, I embody the essence of a data ninja with a creative spark! Proficient in dissecting datasets, my true passion lies in blending data with imagination to craft compelling visual tales. Beyond data realms, I transform moments into visual marvels through editing. Join me in the vibrant landscape of data science and visual storytelling, where we sculpt narratives with numbers, infuse pixels with poetry, and explore Machine Learning and Artificial Intelligence to unlock new possibilities!
Skilled in Python with expertise in libraries like NumPy, Pandas, Scikit-learn, and TensorFlow. Proficient in deep learning and practicle implementation in regression, classification, and model optimization.
Competent in PowerBI for data modeling, report creation, and DAX implementation. Proficient in Tableau for creating interactive dashboards and visually appealing reports to communicate insights effectively.
Skilled in SQL, particularly MySQL, for database management and querying, and MongoDB for handling unstructured data. Capable of designing and optimizing database schemas for efficiency.
This project aims to predict traffic volume in urban environments using Temporal Convolutional Networks (TCNs). Leveraging the Metro Interstate Traffic Volume time-series dataset from 2012-2018, the project addresses the challenge of congestion prediction, crucial for effective traffic management and urban planning.
This project involves analyzing and visualizing sales data from the Olist dataset using SQL and PowerBI. It provides insights into customer behavior, product performance, and sales trends, facilitating strategic decision-making for the business.
The "Student Performance Prediction" project uses modular programming in Python to build a flexible ML system. It leverages Pandas, NumPy, and Scikit-learn for data processing and model training. With modular components for data handling and model training, the project ensures code reusability and scalability. CatBoost enhances model accuracy, while Flask enables a simple user-friendly interface.
The "Text-to-SQL Gemini App" effortlessly transforms English queries into SQL commands using Google's Generative AI, Gemini. Built with Python and Streamlit, this intuitive web application simplifies database interactions. With SQLite managing the database, users can input natural language questions and receive accurate SQL outputs instantly. Git ensures seamless collaboration, while Markdown provides clear documentation. Streamlit enhances interactivity, creating a user-friendly experience.
I'm currently looking for new opportunities, my inbox is always open. Whether you have a question or just want to say hi, I'll try my best to get back to you!