• 🎓 Information Technology Graduate from the University of Mumbai.
• 💻 Data Scientist & AI Enthusiast with experience in Machine Learning, Deep Learning,Data Wrangling,NLP.
• 🎯 Interested in NLP, Data Visualization, and Model Efficiency.
• 🏆 Kaggle Competitor: Achieved top 368 in a recent competition.
• 📚 Passionate about learning and sharing knowledge on AI and data science.

• Programming Languages: Python, SQL
• Libraries/Frameworks: Pandas, NumPy, TensorFlow, Scikit-learn, PyTorch
• Databases: MySQL, MongoDB
• Other Tools: Git, Docker, Jupyter Notebooks

• Linkedin
• Kaggle

1. Project 1: News Summarization

   • The project aims to quickly convey the main ideas and essential details of a news story, eliminating the need to read the entire article, by utilizing the Hugging Face Google Pegasus pre-trained model and the CNN/Daily Mail dataset..
   • An interactive website built with Flask displays the summarized content, with evaluation performed using ROUGE metrics.

2. Project 2: sagemaker-flight-prices-prediction

   • Developed machine learning project that can predict the price of flight based on date, duration, destination, airline. For this project we use aws sagemaker to train model and also deploy it using streamlit.

3. Project 3: EDA on Terrosim

   • Comprehensive Data Analysis: Conducted an exploratory data analysis (EDA) on the Global Terrorism Database to uncover patterns, trends, and insights related to terrorist activities globally, including attacks by year, region, and target types.

   • Visual Insights and Risk Assessment: Utilized data visualization techniques to highlight the most affected countries, tactics used, and evolving threat levels, offering actionable insights for policymakers and security agencies.

4. Project 4: Image Classification Android App

   • The app uses machine learning algorithms to identify images, leveraging pre-trained model for accurate predictions on JPEG and PNG formats. Its user-friendly interface allows easy image selection from the device's camera or gallery.
   • The app displays the top predicted labels for each image, providing users with clear classification results.

• Rohlik Orders Forecasting Challenge
  • Achieved ranking of 368 on the leaderboard.
  • Engaging in this competition to forecast customer orders for the Rohlik online grocery store. The challenge involves leveraging time series analysis and machine learning techniques to improve order predictions.

• Codecademy - Adam Optimization Documentation
  • Authored detailed documentation for the Adam optimization algorithm. The contribution includes:
  • Overview: Described the importance and usage of Adam optimization in machine learning.
  • Algorithm Details: Provided an explanation of the algorithm's underlying mathematics, including momentum and adaptive learning rates.
  • Implementation: Illustrated with code snippets to demonstrate how Adam can be used across popular ML frameworks like TensorFlow.

Feel free to connect with me on LinkedIn or send an email to [[email protected]] if you want to collaborate or just chat about data science and AI.

Thanks for stopping by! 😄