What Happens if We Use a Mean Squared Error Loss for Binary Classification?

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

Neural Network implemented with different Activation Functions i.e, sigmoid, relu, leaky-relu, softmax and different Optimizers i.e, Gradient Descent, AdaGrad, RMSProp, Adam. You can choose different loss functions as well i.e, cross-entropy loss, hinge-loss, mean squared error (MSE)

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.

This project used various machine learning algorithms to predict rainfall.

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

All things around ... Regression

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

A collection of TypeScript-based machine learning helpers.

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.

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.

PyTorch implementations of the beta divergence loss.