As a passionate data scientist, I believe in the power of data to solve complex problems and drive innovation. I'm also highly interested in the research, design and development of ML and Deep Learning solutions.

Below are some of the projects I've worked on that best showcase my skills and approach to data science.

• Overview: Developed a crime mapping app using Python and C. Implemented A* algorithm variation for pathfinding. When computing the best route between two points, it takes in account real time crime data in order to suggest the fastest & safest route.
• Technologies Used: Python, C, Overpass API, Selenium + BeautifulSoup, Google Maps API, Matplotlib
• Key Highlights: : Algorithm Design (A*), Data Flow, Data Parsing, Geospatial Analysis, Data Visualization, Web scraping.
• GitHub link to the project

• Overview: Developed a ML model for forecasting a company's sales in the healthcare industry. Focused on Time Series Analysis for extracting information of time-dependent features such as trends, seasons,...
• Technologies Used: Python, Pandas, LightGBM, Latitude
• Key Highlights: Time Series Forecasting, Data cleaning, Lag features, Rolling Features, Feature engineering, LightGBM model
• [GitHub link to the project](GitHub link)

• Overview: In the Datathon FME 2023, our team developed an innovative AI tool that recommends outfits aligning with a brand's core philosophy. The challenge was to integrate diverse data types - from tabular data to image features. Our solution involved merging product data with features extracted using a Convolutional Neural Network (CNN), feeding this rich dataset into a Transformer model to generate brand-aligned outfit suggestions.
• Technologies Used: Python, Pandas, TensorFlow, Matplotlib, Jupyter Notebook
• Key Highlights: Data cleaning, Data preprocessing, Feature extraction, Dimensionality reduction, Fill-in-the-blank, Convolutional Neural Networks, Transformer model, Deep learning
• GitHub link to the project

For more projects, check out my GitHub repositories.

• Programming Languages: Python, R, C++, C, Dart, Java
• Data Analysis Tools: Pandas, NumPy, SciPy
• Machine Learning Libraries: Scikit-Learn, TensorFlow, Keras, Pytorch
• Deep Learning Frameworks: OpenMMLab, SLM Lab
• Data Visualization: Matplotlib, Seaborn
• Database Management: SQL, NoSQL, Firebase
• Software Frameworks: Flutter, Django
• Others: Git, Jupyter Notebooks

I'm always open to discussing data science and new opportunities. Let's connect!

• LinkedIn: guimCC
• Email: [email protected]