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c-kosasih/README.md

๐Ÿ‘‹ Hello, world! I'm Clarissa Beatrice Kosasih

๐ŸŽ“ I'm an undergraduate Data Science major at BINUS University (currently in my 5th semester)
๐Ÿ” Actively seeking opportunities in the Data Science and Machine Learning fields
๐Ÿ“ Based in Indonesia ๐ŸŒ

๐Ÿ‘€ About Me

  • ๐Ÿ’ก Deeply curious in Machine Learning, especially in unraveling patterns in the financial sector โ€” like fraud detection and risk optimization ๐Ÿ’ณ๐Ÿ“Š
  • ๐ŸŒฑ I love learning new things โ€” whether itโ€™s tools, techniques, or ideas โ€” and Iโ€™m always up for growing through collaboration and new experiences!
  • ๐Ÿค Open to collaborations, new connections, and fun challenges!

๐Ÿ““ Projects Notebook

๐Ÿ› ๏ธ Skills & Tools

๐Ÿ‘ฉโ€๐Ÿ’ป Programming & Scripting

Python R SQL Markdown

๐Ÿ“š Data Science & Machine Learning

Pandas NumPy Scikit-learn GridSearchCV TensorFlow Keras

๐Ÿงฉ Models I Have Worked With

XGBoost Random Forest Decision Tree CatBoost SVM KNN Logistic Regression Linear Regression AdaBoost

๐Ÿงฐ Tools & Workflow

Git GitHub Google Colab Jupyter Notebook VS Code FastAPI Streamlit Kaggle Figma


๐ŸŒ Web Dev Basics

While not directly tied to Data Science, I learned these during my university coursework

HTML CSS JavaScript

๐Ÿ“Š GitHub Stats

Clarissa's GitHub stats

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  1. c-kosasih c-kosasih Public

    Config files for my GitHub profile.

    1

  2. Hotel-Booking-Cancellation-Prediction-App Hotel-Booking-Cancellation-Prediction-App Public

    Streamlit app that predicts hotel booking cancellations using a Random Forest Classifier based on reservation and guest details.

    Python

  3. Predict-Abalone-Ring-FastApi Predict-Abalone-Ring-FastApi Public

    Predicting abalone age (ring count) using a Random Forest Regressor. The model is deployed via a FastAPI backend for efficient and scalable predictions.

    Jupyter Notebook

  4. Cirrhosis-Multiclass-Classification Cirrhosis-Multiclass-Classification Public

    Multiclass classification of liver cirrhosis stages using clinical data. Compares Random Forest vs. XGBoost with SMOTE for class imbalance and hyperparameter tuning for optimization. Aims to supporโ€ฆ

    Jupyter Notebook

  5. Clustering-Clothing-Company-Customers Clustering-Clothing-Company-Customers Public

    Customer segmentation using K-Means clustering with PCA. Identifies product preferences to enable targeted promotions and personalized marketing strategies.

    Jupyter Notebook

  6. Game-Recommendation-System Game-Recommendation-System Public

    A content-based recommender that suggests games by combining features into a soup feature. Uses TF-IDF to compute similarity and deliver personalized recommendations.

    Jupyter Notebook