This is First Project of Machine Learning by me
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Updated
Jun 28, 2020 - Jupyter Notebook
This is First Project of Machine Learning by me
Model Building and Testing using Ridge, Lasso and ElasticNet Methods
Data Models in R for Multiple Linear Regression and three models (Ridge, Lasso, and Elastic-Net), to predict Medicare claim costs of Type 2 diabetes patients with other diagnoses. We used Data from Entrepreneur’s Medicare Claims Synthetic Public Use Files (DE-SynPUFs) for our analysis.
End-to-end machine learning regression model for predicting housing prices in Bengaluru, with Heroku deployment.
Regresión Lineal Múltiple con Modelos Regularizados (Lasso y Ridge) y Sin Regularizar
Practical Implementation of Linear Regression on Boston Housing Price Prediction
Practical Implementation of Linear Regression on Algerian Forest Fire Dataset.
Building Advanced regression models (Lasso and Ridge) for house price prediction in the Australian market
Sale trending
Metis project 2/7
School exercise - Multivariate Statistical Methods subject
In this series of notebooks, we will dive into each step of the data analysis process of a data set with some information about a list of cars and several attibutes, including their prices. So essentially we will develop a model to predict cars price.
This model trains according to the data and makes a Polynomial Regression curve of degree 16. The model is regularized using Ridge regression. It also compares the predicted values with original outputs and for different alphas.
A small project addressing a regression problem explains implementation of multiple linear regression techniques, hyperparameter tuning, collinearity, model overfitting and complexity using LASSO, Ridge and Elastic net
Sub-seasonal temperature and heatwave prediction in Central Europe with AI (linear and random forest machine learning models)
House Price Prediction can help the customer to arrange the right time to Purchase a House. It is An - ML based Approach which Predicts the Estimated Price of Housing in Mumbai City.
Forest Fire Data
Gemstone Price Prediction - End to End ML Project with AWS deployment
Regression models(lasso, ridge, DT) using NumPy.
A series of Statistical Modelling assignments with the use of R. Applications of Linear, Polynomial, Logistic and Poisson Regression in various datasets
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