sumitdgr Goto Github PK

analyzing-historical-stock-revenue-data-and-building-a-dashboard

automatidata_project

Automatidata is consulting for the New York City Taxi and Limousine Commission (TLC). New York City TLC is an agency responsible for licensing and regulating New York City's taxi cabs and for-hire vehicles. The agency has partnered with Automatidata to develop a regression model that helps estimate taxi fares before the ride.

employee_management_system

I developed this employee management system using PYTHON, TKINTER and SQL working on Visual Studio Code and MySQL.

house-sales-in-king-county-usa---ibm-assignment

ibm_data_analytics_capstone_project

I have utilized skills from the IBM Data Analyst Professional Certificate to address real-world business challenges as Associate Data Analysts..

netflix_analysis_and_visualisation_project

I analyzed the Netflix content and visualized it.

online-grocery-site-frontend

This project uses HTML, CSS and JAVASCRIPT for developing frontend for a online grocery site.

project_covid19_data_analysis

Analysing covid-19 situation for different countries.

salifort_motors_project

Salifort Motors faces high employee turnover. Leadership aims to predict and address it. HR surveys employees to identify reasons. They want a data professional to analyze the data and build a model predicting departures, potentially using statistical or machine learning methods.

stock-price-prediction-machine-learning

Machine learning algorithm to predict if the stock price will increase tomorrow. If the algorithm says that the price will increase, we'll buy stock. If the algorithm says that the price will go down, we won't do anything.

testing

testing

tik_tok_project

TikTok is working on the development of a predictive model that can determine whether a video contains a claim or offers an opinion. With a successful prediction model, TikTok can reduce the backlog of user reports and prioritize them more efficiently.

waze_project

This project is part of a larger effort at Waze to increase growth. Typically, high retention rates indicate satisfied users who repeatedly use the Waze app over time. Developing a churn prediction model will help prevent churn, improve user retention, and grow Waze’s business.