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Achievement: Pull Sharkx2Achievement: Quickdraw

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Dhruv-Limbani/README.md

Hi 👋, I'm Dhruv Limbani

Hello! I'm Dhruv, a graduate student at Columbia University pursuing MS in Computer Science with a focus on Machine Learning. I completed my Bachelor's in Computer Science and Engineering at SRM Institute of Science and Technology, where I developed a passion for solving real-world problems using Machine Learning, Computer Vision, Natural Language Processing, and Generative AI.

All of my current and previous projects, as well as the research work I conducted during my bachelor's, incorporate:

  1. Exploratory Data Analysis, Visualization, and Pre-processing (NumPy, Pandas, Matplotlib, Seaborn)
  2. Machine Learning algorithms (Scikit-learn)
  3. Dense, Convolutional, and Recurrent Neural Networks (TensorFlow, Keras)
  4. Generative Adversarial Networks (TensorFlow, Keras)
  5. Hyperparameter tuning and model evaluation (Scikit-learn)
  6. Building API endpoints (FastAPI)
  7. Developing Web apps (Streamlit)

Throughout my journey in machine learning, I have worked with tabular, visual, and textual data, some of which relate to the academic, finance, and healthcare industries.

I would love to explore more state-of-the-art (SOTA) advancements in Machine Learning, Deep Learning, Computer Vision, and Natural Language Processing, and I am looking forward to conducting research and working with other different forms of data, such as audio, to broaden my familiarity with various algorithms, architectures, and data types.

You can reach out to me at djl2204@columbia.edu if you have any internship opportunities for Summer 2025 that align with my current work, or if you are looking for someone to collaborate on a project or research work.

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  1. Pediatric-Pneumonia-Detection Pediatric-Pneumonia-Detection Public

    Pediatric Pneumonia Detection through GAN-Based Data Augmentation using deep learning models, including CNN and transfer learning with VGG16, on chest X-ray images.

    Jupyter Notebook

  2. German-Credit-Data-Analysis-and-Modeling German-Credit-Data-Analysis-and-Modeling Public

    This project analyzes the German Credit dataset to identify key factors influencing credit decisions and predict creditworthiness. It includes data cleaning, EDA, feature engineering, and model bui…

    Jupyter Notebook

  3. NoCodeML NoCodeML Public

    A No-Code ML Model Building Platform enabling users to perform data cleaning, transformation, visualization, and machine learning model building without writing any code.

    Python

  4. Superstore-Sales-Data-Analysis Superstore-Sales-Data-Analysis Public

    Sales data analysis project with an ETL pipeline built using Power Query. Key insights include sales performance, regional and product analysis, customer segmentation, and shipping trends. Visualiz…

    1

  5. Online-Banking-System Online-Banking-System Public

    Automating banking operations using Python, MySQL, and Streamlit, and providing essential features such as account management, transaction history, credit card and loan applications, and more.

    Python

  6. Financial-Sentiment-Analysis-using-NLP Financial-Sentiment-Analysis-using-NLP Public

    Analyzing and modeling a sentiment-labeled text dataset through preprocessing, feature engineering, and applying machine learning and deep learning models. The work is divided into multiple noteboo…

    Jupyter Notebook