All things around ... Regression

A small code for understanding linear regression.

Life expectancy, an estimate of the number of remaining years of life a person has, is an important consideration for making clinical decisions in primary care. Predicting Life Expectancy helps analyze the average lifespan of the countrymen which helps in making crucial health decisions.

An analysis on how different parameters affect housing prices in Mexico

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

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

PyTorch implementations of the beta divergence loss.

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

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

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…

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)

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”

This project used various machine learning algorithms to predict rainfall.

Bayesian Regression of Latent Source Modelling for Predicting Price Variation of Bitcoin

Machine Learning for Data 3141 Reichman University Spring 2022 - 6 Homework Projects

Linear Regression on Medical Insurance Dataset

IJCAI 2021, "Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation"

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

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

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