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  • Manchester, United Kingdom

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MohiniDeshpande/README.md

👋 Hi, I’m Mohini Deshpande

Welcome to my GitHub profile! I'm a passionate data scientist with a keen interest in machine learning and computer vision.

👀 I’m interested in:

  • Data Science
  • Machine Learning
  • Computer Vision

🌱 I’m currently learning:

  • Advanced machine learning algorithms
  • Deep learning techniques for computer vision
  • Real-time data processing and analytics
  • Data Engineering and Natural Language Processing

💞️ I’m looking to collaborate on:

  • Innovative projects in data science and machine learning
  • Open-source contributions related to computer vision
  • Research projects that involve predictive modeling and analysis

📫 How to reach me:

😄 Pronouns:

  • She/Her

Projects

Here are some of the projects I've worked on:

  1. Bank Churn Prediction: Developed a predictive model to identify customers likely to leave the bank using various classification algorithms. Achieved an accuracy score of 94.31%.

  2. Steel Defect Detection Using Deep Learning: Developed an end-to-end solution for detecting defects in steel surfaces using a ResNet152V2 model for image classification and bounding box prediction. The model was fine-tuned using pre-trained weights on ImageNet and achieved high accuracy of 97.3%. Link to this project: Steel Defect Detection

Currently I'm trying to upload my projects that I have saved locally on here to add on to my portfolio.

Feel free to check out my repositories and contribute to my projects!

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  1. Bank-Customer-Churn-Prediction Bank-Customer-Churn-Prediction Public

    This project implements various machine learning algorithms to predict customer churn in a banking dataset. By analyzing customer data, the model identifies patterns that indicate whether a custome…

    Python

  2. Steel-Defect-Detection Steel-Defect-Detection Public

    This project is a Steel Defect Detection System using a ResNet152V2-based deep learning model. The model predicts bounding boxes for steel defects in images and classifies them into multiple defect…

    Python