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PoojaBPatil2309/README.md

πŸ‘‹ Hello, I am Pooja Patil

🧠 Passionate about applying Data Science, Machine Learning, and NLP to solve real-world problems.


πŸ”­ Currently Working On

  • πŸ§ͺ Exploring various feature selection techniques to better understand their impact on model performance and interpretability.

🌱 Currently Learning

  • πŸ€– Studying Agentic AI β€” how intelligent agents make autonomous decisions in dynamic environments.

πŸ› οΈ Tech Stack & Skills

πŸ‘©β€πŸ’» Languages

  • Python
  • SQL

βš™οΈ Technologies & Frameworks

  • TensorFlow, PyTorch, MeVisLab, AWS, GenAI
  • Scikit-learn, XGBoost, LightGBM, Statsmodels
  • OpenCV, Pandas, NumPy

🧠 Core Skills

  • Machine Learning, Deep Learning, Ensemble Learning
  • Feature Engineering & Feature Selection
  • NLP, Data Analytics, Model Evaluation, Data Preprocessing
  • Computer Vision

πŸ”§ Tools & Platforms

  • Git & GitHub, Jupyter Notebook, Google Colab, VS Code

Popular repositories Loading

  1. Mental-Stress-Detection- Mental-Stress-Detection- Public

    This project developed a system to detect mental stress based on textual data, utilizing NLP techniques and ML algorithms to analyze and classify text for stress levels.

    Jupyter Notebook

  2. SMS-Spam-Detection SMS-Spam-Detection Public

    This project aimed to develop an automated system for identifying spam messages in SMS using Natural Language Processing (NLP). By analyzing the content of SMS text data, the system classifies mess…

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  3. Alert_crush_injuries_on_power_press_machine Alert_crush_injuries_on_power_press_machine Public

    Alert crush injuries on power press machine

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  4. PoojaBPatil2309 PoojaBPatil2309 Public

  5. PCOS-Prediction-using-Feature-Selection-and-Ensemble-Learning PCOS-Prediction-using-Feature-Selection-and-Ensemble-Learning Public

    Machine learning framework for PCOS prediction using GA, MI, Boruta, and hybrid feature selection with ensemble learning.

    Jupyter Notebook

  6. Text-Summarizer Text-Summarizer Public

    Summarizes large chunks of data

    Python