Using machine learning to discover the best location for Oily Giant to open their next well, based on reserve volume and profit

The "Advertising Impact Analysis" project aims to analyze the relationship between advertising expenditure across different channels (such as TV, radio, online) and its impact on sales or revenue.

Create a simple, univariate linear regression model that predicts the salary from a person's experience (measured in years), using the gradiant descent algorithm.

Prediction model for profit of 50 startups dataset by Multiple Linear Regression

Comparing Ridge and LASSO model to find the best accuracy for Home Price Prediction

Intrusion Detection System for MQTT Enabled IoT.

We build a model to predict the value of used cars, while also considering speed and quality of the prediction.

Beta Bank is losing customers monthly. Employees want to focus on client retention. As a Data Scientist, I created a model to predict the chance of a customer leaving, based on past behavior and contract terminations.

💎 'The Linear Regression Challenge: Diamonds Price Prediction' @ironhack Data Analytics Bootcamp

An analysis on how different parameters affect housing prices in Mexico

Linear Regression on Medical Insurance Dataset

Elastic net project

In this Notebook, MSE of three models (LinearRegression, Polynomial, and 3-layer Neural Network using Keras) has calculated and compared

In this repository you will find the complete implementation of the model proposed in the paper entitled “Wildfire prediction using zero-inflated negative binomial mixed models: Application to Spain”

Create a prototype for a machine learning model to predict the amount of gold recovered from gold ore.

In the digital music era, understanding artist popularity on Spotify is vital. This project taps into Spotify's data, analyzing key factors driving artist prominence. Through our insights, we illuminate what sets successful artists apart in this dynamic platform.

This project provided practice with logistic regression and the cost functions MSE and log loss

Data in the social networking services is increasing day by day. So, there is heavy requirement to study the highly dynamic behavior of the users towards these services. The task here is to estimate the comment count that a post is expected to receive in next few(H) hours. Data has been scraped from one of the most popular social networking site…

Infidelity and Marital Satisfaction investigation using elastic net

This repository provides topics in PyTorch which is used for Deep Learning