Portfolio

Repository containing portfolio of software development, data engineering, and data science projects completed by me for academic, self learning, and hobby purposes. Presented in the form of Python files, Jupyter Notebooks, SQL and Tableau etc.

For a more visually pleasant experience for browsing the portfolio, check out lafirm.github.io

The Tableau portfolio is located here.

Instructions for Running Python Notebooks

1. Run notebooks locally on your machine by using Jupyter Notebook Server, click here for more details.
2. To easily run our notebooks without any installations on our local machine, we can use cloud services like Binder, Google Colab, Kaggle etc., click here for more details.

Contents

• Machine Learning

  • Walmart Weekly Sales Prediction Model: A model to predict the department-wide weekly sales for each Walmart store using various statistical analysis tools. Identified the best sales amount of a walmart store utilizing machine learning.

  Tools: Scikit-Learn, Pandas, Seaborn, Matplotlib

  • Bengaluru House Price Prediction Model: A model trained to predict the Bengaluru real estate price using Scikit-Learn and deployed on Heroku (blrhouseprice.herokuapp.com) using Docker and Github Actions.

  Tools: Scikit-Learn, Pandas, Numpy, Docker, Heroku

• Data Analysis and Visualisation

  • Python

    • Heart Failure Analysis: Analysis of a small group of Heart Failure Patients.
    • Retail Store Analysis: Exploratory data analysis of the stores operating in the U.S using Pandas, Seaborn for visualization.

    Tools: Pandas, Numpy, Seaborn and Matplotlib

• Web Scraping

  • Python

    • YouTube Trending Videos Scraping: Periodical scraping of Top 10 trending videos on YouTube using Selenium and Github Actions with CRON jobs.
    • Github Top Repositories Scraping: Scraping of Top 30 repositories for each topic on Github using BeautifulSoup and requests library.

    Tools: BeautifulSoup, Selenium, AWS Lambda

• SQL

  • Nashville Housing Dataset - Cleaning: Performed data cleaning operation on Nashville Housing Dataset using SQL
  • 8 week SQL Challenge: This project contains all of my code submissions for the #8WeekSQLChallenge!

  Tools: MySQL, MS-SQL and SSMS

• Micro Projects:

  • Python
    • ML with Linear Regression: Using Linear Regression to predict the percentage of marks scored by a student.
  • Excel
    • Bike Sales Analysis: Performed data cleaning, analysis and created dashboards using Pivot Table in MS-Excel
    • Kevin Cookie Company Analysis: Analysed Kevin Cookie Company dataset and created dashboards using Excel.

I also dabble in all other kinds of technology. You can find a general portfolio here.

If you liked what you saw, want to have a chat with me about the portfolio, work opportunities, or collaboration, message me @lafirm.

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