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#

scikit-learn-api

Here are 32 public repositories matching this topic...

A garden for scikit-learn compatible trees

  • UpdatedJun 20, 2024
  • Python

Random Forest or XGBoost? It is Time to Explore LCE

  • UpdatedAug 15, 2023
  • Python
Machine-Learning-with-Scikit-Learn-Python-3.x

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…

  • UpdatedJun 16, 2021
  • Jupyter Notebook

Base classes for creating scikit-learn-like parametric objects, and tools for working with them.

  • UpdatedDec 15, 2025
  • Python

AutoML - Hyper parameters search for scikit-learn pipelines using Microsoft NNI

  • UpdatedDec 8, 2022
  • Python

Machine Learning project to predict popularity of Instagram posts

  • UpdatedSep 7, 2017
  • Python

The sslearn library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.

  • UpdatedJul 16, 2025
  • Python

Gender Classifier, Price Predictor, Human Behavior Predictor and other Insights from Machine Learning.

  • UpdatedOct 31, 2019
  • Jupyter Notebook

Analysis of market trend using Deep Learning is project that forecasts stock prices using historical data and ML models. Leveraging data collection, feature engineering, and model training. Primarily designed for the Indian stock market, it is adaptable for international markets, providing valuable insights for investors and analysts.

  • UpdatedAug 4, 2024
  • Jupyter Notebook

A package for fitting regularized models from scikit-learn via proximal gradient descent

  • UpdatedJun 28, 2023
  • Python

A scikit-learn compatible implementation of Bumping as described by “Elements of Statistical Learning” second edition (290-292).

  • UpdatedApr 1, 2020
  • Python

A python implementation of the Generative Topographic Mapping

  • UpdatedSep 6, 2018
  • Python

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.

  • UpdatedSep 27, 2023
  • Jupyter Notebook

Hierarchical Multi Class validation metrics:HMC-loss

  • UpdatedApr 24, 2017
  • Python

24/01/2024 Jeyfrey J. Calero R. Aplicación de Redes Neuronales con scikit-learn streamlit, pandas, seaborn y matplolib

  • UpdatedMar 9, 2024
  • Python

Scikit-learn (sklearn) projects in form of Jupyter Notebooks

  • UpdatedFeb 10, 2019
  • Jupyter Notebook

This repository contains the machine learning examples in anaconda-python

  • UpdatedJan 18, 2019
  • Python

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