Polynomial Regression
Polynomial Regression is used to find the coefficients of functions where the relationship between input data and output data are non-linear. In particular, the methodology attempts to use an n-th degree polynomial to fit the data. The articles and projects on this topic are listed below.
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Linear Regression
Linear Regression is used to find the coefficients of functions where there is a linear relationship between the input data and the output. The articles and projects on this topic are listed below.
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Machine Learning Metrics
Several metrics are used in Machine Learning to evaluate the performance of methodologies in order to be able to compare and select the most suitable one for specific problems. This sections provides details to the most common and well-known metrics used.
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Intro to Artificial Intelligence and Machine Learning
The article provides a short introduction to AI and ML so that the reader can familiarize with some of the main concepts and goals of these fields. Click the button below to access it.
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Latest AI and ML Pages
- [1] Python code of common Regression Metrics from scratch and also by using sklearn
- [2] Interactive Polynomial Regression Code modifiable by the user in Javascript
- [3] Polynomial Regression is used to predict Coronavirus cases with scikit-learn
- [4] An example problem which uses Polynomial Regression: The Rescue Mission
- [5] Code of Polynomial Regression created from scratch in Python using only main equations
Top AI and ML Pages
- [1] Introduction to Artificial Intelligence and Machine Learning
- [2] Details and formulas of some common Regression Metrics: MAE, RMSE, MSE, R2
- [3] Introduction to Linear Regression, main equations and concepts
- [4] Introduction to Polynomial Regression, main equations and concepts
- [5] Linear Regression is used to predict the house prices with scikit-learn