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Deialima/README.md

Hi, I'm Andreia Lima 👋

Data Analyst | Aspiring Data Scientist | Machine Learning & AI

I build data-driven solutions using Python, SQL, Machine Learning, and Data Analytics to transform complex datasets into actionable business insights.

I'm passionate about solving real-world business problems through Exploratory Data Analysis (EDA), Statistical Analysis, Predictive Modeling, Natural Language Processing (NLP), and Machine Learning.

Currently completing the TripleTen Data Science Bootcamp while expanding my knowledge in AI and predictive analytics.

🛠️ Tech Stack

My Skills

Programming Languages

  • Python
  • SQL

Data Analysis

  • Pandas
  • NumPy
  • Data Cleaning
  • Exploratory Data Analysis (EDA)
  • Statistical Analysis
  • Hypothesis Testing
  • Feature Engineering

Machine Learning

  • Scikit-learn
  • Supervised Learning
  • Classification
  • Regression
  • Natural Language Processing (NLP)
  • Model Evaluation

Data Visualization

  • Matplotlib
  • Plotly
  • Tableau
  • Power BI

Development Tools

  • Git
  • GitHub
  • Jupyter Notebook
  • VS Code

🌱 Currently Learning

  • Deep Learning
  • Neural Networks
  • Computer Vision
  • Unsupervised Learning
  • Artificial Intelligence

📊 GitHub Stats

Andreia's GitHub stats

Top Languages

📬 Let's Connect

LinkedIn

Gmail

🎯 Career Goal

I'm currently seeking opportunities as a Data Analyst or Junior Data Scientist, where I can apply data analytics and machine learning to solve real business problems while continuing to grow as an AI professional.

⭐ Thanks for visiting my GitHub profile!

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  1. Carlytics Carlytics Public

    Interactive dashboard for exploring used car listings data, built with Python, Streamlit and Plotly. Deployed on Render.

    Python

  2. Music-Streaming-Analysis Music-Streaming-Analysis Public

    This project analyzes music streaming data from Springfield and Shelbyville to compare user behavior and test data-driven hypotheses about listening preferences and activity patterns.

    Jupyter Notebook

  3. Project-Store-One Project-Store-One Public

    As part of the analytics team, I evaluated the quality of collected data samples, identified inconsistencies and missing values, and prepared the dataset for future analysis and modeling.

  4. instacart-eda instacart-eda Public

    End-to-end EDA on Instacart grocery orders dataset — data cleaning, preprocessing and customer behavior analysis using Python and Pandas.

    Jupyter Notebook

  5. Megaline-Telecom Megaline-Telecom Public

    This project analyzes customer behavior data from Megaline Telecom to understand usage patterns and compare two mobile plans: Smart and Ultra.

    Jupyter Notebook