This is a reviewed notebook to the DSN AI+ OAU July 2020 challenge where I took the first position. The project demonstrate proper Exploratory Data Analysis, categorical data handling, Data visualization, feature selection and engineering, Model selection and hyperparameter tuning of various regression algorithms.

Oasis Infobyte Internship Projects one month of Internship as a data science intern at Oasis Infobyte. The Data Science Internship Offers Practical Work Experience And An Introduction To Creating Machine Learning Models And Improving Data Driven Technologies knowledge. This Internship Will Involve Challenging Opportunities, Real World Projects.

This is a data challenge to predict future store sales using past store sales. The data was more than 10 Gigabytes across years and retail stores across the United States. Unfortunately, due to an NDA signed, the original data cannot be shared. To see a more demonstrable version of the problem statement and proposed solutions, please see the Pow…

Utilizing facebook-prophet machine learning model to analyze MercadoLibre's financial and user data to identify search traffic trends and predict stock prices and sales revenue.

Data Science Internship at Oasis InfoByte July - August 2023

A Sales Data and product predictions data set project.

This repository contain an EDA and Machine Learning models to predict the sales of a mobile phone distributor company.

Tasks and Projects completed during the Data Science internship at CODSOFT

Applied ML techniques to maximize Black Friday sales revenue

The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and predict the sales of each product at a particular outlet.

Doing predictions of sales for Qatar-based user. Used timeseries, seasonal decomposition and sentiment analysis. Goal was to visualize sales, find connections between hundreds of independent variables and sales and to make the sales of the company and make them better.