My solution to House-Prices Advanced Regression Techniques, A beginner-friendly project on Kaggle.
Regression Machine Learning Project
Metis project 2/7
Genetic assignment of individuals to known source populations using network estimation tools.
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.
Predicting house price
House-Prices Advanced Regression Techniques Competition Solution
A repository containing machine learning projects and models.
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.
Nextflow pipeline integrating TCGA multi-omics with MOFA and downstream LASSO to reveal tissue-specific oncogene selection pressures
"Learning R for data scientists." This phrase describes the process of acquiring the skills and knowledge necessary to use the R programming language for data analysis.
Built a Gradient Boosting model by employing Lasso Regularization and Hyper-parameter tuning
NYU CSCI-GA 3033 Final Project
Regression models(lasso, ridge, DT) using NumPy.
Repository about the projects in the course of Modeling and control of cyberphysical systems at PoliTo in 2022/2023
Advanced Regression model on Housing Data from Australia for my Upgrad - IIITB AI ML PG Course
Practical Implementation of Linear Regression on Boston Housing Price Prediction
ML | Regression Analysis| Random Forest| XGBoost| Gradient Boost| EDA| Feature Engineering| Feature selection
Analysis and Modelling data from King county housing data
This is a project developed as part of the Foundations of Data science course at New York University
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