Python regression and probabilities snippets
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Updated
Jul 16, 2024 - Jupyter Notebook
Python regression and probabilities snippets
Echo State Networks for Time Series Forecasting
Here the prediction and analysis of student scores using selected features is done entirely by linear regression machine learning algorithm. This project covers all methods of linear regression theory.
PhD thesis supplementary materials
Machine Learning Regression Model to Predict Energy Efficiency of Buildings
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
Slides for the 26th International Conference on Computational Statistics (COMPSTAT 2024)
📗 This repository provides an in-depth exploration of the predictive linear regression model tailored for Jamboree Institute students' data, with the goal of assisting their admission to international colleges. The analysis encompasses the application of Ridge, Lasso, and ElasticNet regressions to enhance predictive accuracy and robustness.
This repository contains the code and data necessary to reproduce the results presented in the paper "Ridge Regularization for Spatial Auto-regressive Models with Multicollinearity Issues" submitted to Advances in Statistical Analysis (AStA).
Prediction of Insurance Charges using Regression
Predicting Baseball Statistics: Classification and Regression Applications in Python Using scikit-learn and TensorFlow-Keras
As part of the UCSanDiego online course "Machine Learning Fundamentals"
A taxi company called Sweet Lift has collected historical data on taxi orders at the airport and they need to predict the number of taxi orders for the next hour.
Spring/Summer 2024 Research : Socio-Economic effects on COVID-19 Mortality Rates
Machine learning models
Analysis will help Jamboree in understanding what factors are important in graduate admissions and how these factors are interrelated among themselves. It will also help predict one's chances of admission given the rest of the variables.
House Price Prediction using Ridge Linear Regression Model and Bangalore Dataset
A MLR algorithm that analyzes diabetes data in African Americans to predict a diabetes diagnosis
A Ridge regression model used to estimate house prices.
Implementation of algorithms such as normal equations, gradient descent, stochastic gradient descent, lasso regularization and ridge regularization from scratch and done linear as well as polynomial regression analysis. Implementation of several classification algorithms from scratch i.e. not used any standard libraries like sklearn or tensorflow.
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