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smusab9152/README.md

Hi, I'm Musab Parvez Shaikh!

I work with data using Python, SQL, and machine learning to uncover insights and build useful projects. Here on GitHub, I share my analyses, experiments, and ideas with anyone interested in data and technology

Technologies & Tools

  • Programming Languages: Python, R, SQL
  • Data Analysis & Visualization: Pandas, NumPy, Matplotlib, Seaborn
  • Machine Learning: Scikit-learn, TensorFlow, Keras
  • Data Management: MS Excel, SQL Databases, MongoDB
  • Tools & Platforms: Jupyter, Git, GitHub, Kaggle

Featured Projects

Explore some of my repositories to see my work in action:

  • LA Crime Prediction Project - This project looks at crime data from Los Angeles. It cleans and organizes the data, then explores patterns in different types of crimes and locations. Visualizations help show trends and insights clearly. The project also tries to predict future crime patterns. It’s a practical example of using data to understand city crime.
  • Reddit Rules Classification - This project uses machine learning to determine whether Reddit comments follow subreddit rules. It processes the text of comments to predict if they comply with community guidelines. The goal is to help automate moderation by identifying rule-breaking content. This approach can assist in maintaining healthy online communities.
  • Beats Per Minute Prediction - This project predicts a song's Beats Per Minute (BPM) using its various audio features. It cleans the data, applies transformations to normalize skewed feature distributions, and trains several regression models. The goal is to build an accurate model that can determine the tempo of a song from its characteristics, providing a practical example of a regression task.
  • Coffee Sales Dashboard - Explore coffee sales trends with interactive charts and analytics. This dashboard makes it easy to dive into your data, find top products, and spot opportunities—all in one place. With user-friendly visualizations, you can track performance, identify growth areas, and make data-driven decisions for your coffee business.

Get in Touch

Feel free to reach out for collaborations, discussions, or just a friendly chat about technology!

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  1. LA_Crime LA_Crime Public

    This repository contains a data analysis and machine learning project on Los Angeles crime data. It includes data preprocessing, exploratory data analysis (EDA), visualizations of crime trends by t…

    Jupyter Notebook 1

  2. bpm_pred_songs bpm_pred_songs Public

    ML project to predict the Beats Per Minute (BPM) of a song using various audio features. This is a submission for the Kaggle Playground Series (S04E02). The notebook covers a full data science work…

    Jupyter Notebook 1

  3. Reddit_rules_classification Reddit_rules_classification Public

    This project implements a machine learning model to predict whether Reddit comments violate subreddit-specific rules. Using natural language processing (NLP) techniques and a binary classification …

    Jupyter Notebook 1

  4. music_claims music_claims Public

    music_claims helps manage and track music rights and claims, providing tools for copyright management and dispute resolution. It’s ideal for artists, labels, and publishers who need a transparent s…

    1

  5. Coffee_Sales_Analysis_Dashboard Coffee_Sales_Analysis_Dashboard Public

    Explore coffee sales trends with interactive charts and analytics. This dashboard makes it easy to dive into your data, find top products, and spot opportunities—all in one place.

    1

  6. The_Movie_Dataset_Dashboard-Tableau The_Movie_Dataset_Dashboard-Tableau Public

    This repository hosts an interactive Tableau dashboard designed for a deep-dive analysis of "The Movie Dataset." It allows users to visualize and explore trends in film genres, revenue, ratings, an…

    1