This repository contains valuable insights and visualizations derived from an extensive HR dataset spanning from 2000 to 2020, with over 22,000 rows.
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Updated
Jul 19, 2023
This repository contains valuable insights and visualizations derived from an extensive HR dataset spanning from 2000 to 2020, with over 22,000 rows.
Building a sales forecasting model that predicts future sales for each Rossmann store. By leveraging historical sales data, store-specific information, and external factors
This project endeavors to create a recommendation system that suggests products to users based on their historical interactions and preferences.
I explore and analyze the complex landscape of international debt, aiming to gain insights into the debt trends and their impact on economies worldwide.
GreenSight - Analyze and evaluate Environmental, Social, and Governance (ESG) factors for companies. The application provides insights into a company's ESG performance, trends, and impact, offering a comprehensive view of its sustainability practices.
Classifying whether the given event was a signal or a background noise in the process of decay for Higgs particle acceleration.
The Racoon Detection project focuses on using object detection techniques to identify and locate raccoons in images.
In this project, I am analyzing hiring process data to gain insights from about records of previous hires within a multinational company. By analyzing this data, I am aiming to uncover valuable trends and information about the company's hiring process, which can contribute to making informed decisions and improvements for the future.
This project aims to develop machine learning models to forecast PM2.5 levels in the Jeongnim-Dong area from 2018 to 2022.
Welcome to the Consumable Sales Dashboard, a powerful and intuitive data visualization tool built using Power BI. This dashboard offers a comprehensive view of sales data for consumable products, allowing you to quickly and easily analyze performance and identify trends.
This project aims to revolutionize the way banks market to their customers by leveraging machine learning techniques to segment customers based on their account history, credit scores, and demographics.
Getting a rapid understanding of the context of a patient’s overall health has been particularly important during the COVID-19 pandemic as healthcare workers around the world struggle with hospitals
This project aims to analyze the historical trends of Netflix stock prices using Python and data analysis techniques.
Repository is designed to help you strengthen your SQL query skills by providing a collection of common and interview-based SQL queries for practice.
This project is to develop a robust model capable of accurately predicting energy consumption in buildings. This endeavor involves harnessing historical energy usage data in conjunction with diverse weather and environmental variables to construct an effective predictive model.
SummarizeIt is a powerful yet user-friendly Streamlit application designed to quickly generate concise summaries of text content. Whether you're dealing with lengthy articles, research papers, or any other form of textual data, SummarizeIt simplifies the process, providing a convenient way to distill information.
This project, I am constructing a predictive model that can prognosticate gold prices using historical price data and pertinent financial indicators.
This project focuses on the classification of plant seedlings using deep learning techniques. The goal is to develop a model that can accurately identify different types of plant species or determine the health status of seedlings based on input images.
The primary goal of the Customer Lifetime Value Project is to develop a robust framework for predicting the potential value that a customer will generate over the course of their relationship with the business. By analyzing historical customer data and behavior, the project aims to create models that can forecast the expected revenue
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