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Lani-Dom/README.md



👋 Hello! I'm Lani

  • 🔭 As a Product Designer with 11 years of experience, I specialize in creating user-centered solutions driven by data. My expertise in Design, User Research, Machine Learning, and Data Analysis allows me to deeply understand user behavior and deliver impactful products.

  • 🏅 I enjoy working with cross-functional teams from initial research to implementation, as the diversity of perspectives and skills enriches the product creation process. This approach allows me to design solutions that are aligned with the real needs of users, clients, and the market.

⚡Core Competencies in Data Science

  • Data Analysis: Data Treatment (Pandas, NumPy), Data Analysis, Data Cleaning, Exploratory Data Analysis (EDA), Data Visualization (Matplotlib, Seaborn), Feature Engineering, Statistical Analysis

  • Machine Learning Techniques: Time Series, Supervised Learning, Predictive Modeling, Sentiment Analysis, Classification, Regression, Bootstrapping, Model Training (Logistic Regression, Linear Regression, Random Forest, Decision Tree Regressor, Gradient Boosting, XGBoost, LightGBM, CatBoost, Dummy Classifier, etc.)

  • Model Evaluation and Metrics: Hyperparameter Tuning, Cross-Validation, Mean Squared Error, Accuracy Score, F1 Score, ROC AUC Score, Confusion Matrix, Recall Score, etc.


💻 Technologies

Python Tableau SQL HTML CSSS Bootstrap JQuery

Figma Sketch AdobeXD Photoshop Ilustrator After Effects Cinema4D Autodesk Maya Unity

And some more...

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  1. Business-Focused-Machine-Learning Business-Focused-Machine-Learning Public

    This project assesses geological data from three regions using linear regression to predict reservoir volume in potential wells. The goal is to choose the most profitable region with less than 2.5%…

    Jupyter Notebook

  2. Exploratory-Data-Statistical-Analysis Exploratory-Data-Statistical-Analysis Public

    This project builds a predictive system for Interconnect, a telecommunications operator, to anticipate customer churn. Using historical data on contracts, services, and customer characteristics, th…

    Jupyter Notebook

  3. Numerical_Methods Numerical_Methods Public

    This project develops a model for Rusty Bargain to predict the market value of used cars. The model must provide fast and accurate estimates, meeting the platform's quality criteria to enhance the …

    Jupyter Notebook

  4. Supervised-Learning-FinalProject Supervised-Learning-FinalProject Public

    This project builds a predictive system for Interconnect, a telecommunications operator, to anticipate customer churn. Using historical data on contracts, services, and customer characteristics, th…

    Jupyter Notebook

  5. Time_Series Time_Series Public

    This project develops a time series forecasting model for Sweet Lift Taxi to accurately predict taxi demand at airports during the next hour.

    Jupyter Notebook

  6. Machine_Learning_for_Sentiment_Analysis Machine_Learning_for_Sentiment_Analysis Public

    This project develops an automated system to classify movie reviews as positive or negative using a machine learning model trained on IMDb data. The goal is to optimize sentiment analysis and provi…

    Jupyter Notebook