The sslearn library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.
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Updated
Jun 21, 2024 - Python
The sslearn library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.
Base classes for creating scikit-learn-like parametric objects, and tools for working with them.
Quantile Regression Forests compatible with scikit-learn.
Pipelines transformMixin that preserve the format dataframe and automation in correlation
24/01/2024 Jeyfrey J. Calero R. Aplicación de Redes Neuronales con scikit-learn streamlit, pandas, seaborn y matplolib
The "Breast Cancer Classification using Neural Networks" project focuses on predicting the presence of breast cancer using deep learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, and implementing neural networks.
Random Forest or XGBoost? It is Time to Explore LCE
A garden for scikit-learn compatible trees
A package for fitting regularized models from scikit-learn via proximal gradient descent
The transformer that transforms data so to squared norm of transformed data becomes Mahalanobis' distance.
AutoML - Hyper parameters search for scikit-learn pipelines using Microsoft NNI
Notes, tutorials, code snippets and templates focused on scikit-learn API extention for Machine Learning
Contains models implemented from scratch and a project implemented from end-to-end
In general, a learning problem considers a set of n samples of data and then tries to predict properties of unknown data. If each sample is more than a single number and, for instance, a multi-dimensional entry (aka multivariate data), it is said to have several attributes or features. Learning problems fall into a few categories: supervised lea…
The code commited while the code tutorials on yt.
A sample of often unknown and underrated functionalities in scikit learn library.
A scikit-learn compatible implementation of Bumping as described by “Elements of Statistical Learning” second edition (290-292).
Gender Classifier, Price Predictor, Human Behavior Predictor and other Insights from Machine Learning.
classify anyone as either 'male' or 'female' given just their 'height', 'weight' and 'shoe size' (youtube challenge by 'Siraj Raval')
Scikit-learn (sklearn) projects in form of Jupyter Notebooks
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