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Achievement: YOLOAchievement: Pull Sharkx2

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abdullahashfaqvirk/README.md

ɪ'ᴍ ᴀʙᴅᴜʟʟᴀʜ!

Digital Craftsman (AI/ML Developer, Data Scientist)

I am a Data Scientist passionate about AI/ML, with strong technical skills in programming, data analysis and machine learning.

  • ✨ Student of life :)
  • 🏙 Tutor and Mentor at Preply.
  • ❤ Contributing to Open Source.
  • 🌱 I’m currently learning many things, I believe that everyday is a learning opportunity.

abdullahashfaqvirk

Tᴇᴄʜ sᴛᴀᴄᴋ

GIF description

Machine Learning

Scikit-learn, TensorFlow, LangChain, MLflow, NumPy, Pandas, Matplotlib, Seaborn, SciPy

Web Development

Django, FastAPI, React, Tailwind, Bootstrap, CSS, HTML

Database Systems

MySQL, SQL Server, MongoDB

Cloud & MLOps

AWS, Azure, Docker, Git, GitHub Actions


Gɪᴛʜᴜʙ Sᴛᴀᴛs

GitHub Stats

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Top Repo

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  1. Employee-Attrition-Prediction Employee-Attrition-Prediction Public

    A machine learning driven system for predicting employee attrition, featuring statistical analysis, Flask API integration and Dockerized deployment.

    Jupyter Notebook

  2. Online-Retail-Customer-Analysis Online-Retail-Customer-Analysis Public

    A customer behavior analysis project using K-Means clustering and RFM profiling to uncover actionable insights from retail transaction data.

    Jupyter Notebook

  3. Text-Summarization-App Text-Summarization-App Public

    Deploy a Hugging Face Spaces app with a CI/CD pipeline using GitHub Actions, featuring Transformers and Gradio for text summarization.

    Python

  4. PyCapture PyCapture Public

    PyCapture is a desktop application designed to automate screen capturing, allowing users to schedule screenshots at specified intervals.

    Python

  5. Amazon-Laptop-Price-Prediction Amazon-Laptop-Price-Prediction Public

    Developed an Amazon laptop price prediction tool using machine learning algorithms, integrated with a Streamlit app for an interactive user experience.

    Jupyter Notebook 2

  6. Book-Recommendation-System Book-Recommendation-System Public

    A personalized book recommendation system that combines collaborative filtering and popularity-based methods, featuring an interactive HTML/CSS frontend and a Flask backend.

    Jupyter Notebook 3