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ml-predictive-maintenance

riccardoprosdocimi / ml-predictive-maintenance

Star 0

This repository contains code and documentation for a machine learning project focused on predictive maintenance in industrial machinery. The project explores the development of a comprehensive predictive maintenance system using various machine learning techniques.

machine-learning deep-learning pytorch lstm gru rnn artificial-neural-networks logistic-regression mlp data-preprocessing feature-engineering hyperparameter-tuning model-evaluation classifiers predictive-maintenance failure-prediction sequential-models precision-recall auc-roc-curve industrial-machinery
  • Updated May 2, 2024
  • Jupyter Notebook

SubbulakshmiSN / Diabetes_Prediction_application_using_streamlit

Star 1

The Diabetes Prediction Application serves as a valuable tool for individuals to assess their risk of diabetes based on personal health information. By leveraging machine learning techniques, the application provides accurate predictions, aiding users in making informed decisions about their health.

numpy sklearn pandas python3 decision-tree-classifier classifiers streamlit ordinalencoder
  • Updated Apr 3, 2024
  • Jupyter Notebook
Automatic_design_of_quantum_feature_maps_Genetic_Auto-Generation

sergio94al / Automatic_design_of_quantum_feature_maps_Genetic_Auto-Generation

Star 7

Registered Software. Official code of the published article "Automatic design of quantum feature maps". This quantum machine learning technique allows to auto-generate quantum-inspired classifiers by using multiobjetive genetic algorithms for tabular data.

machine-learning qml genetic-algorithm artificial-intelligence quantum-computing evolutionary-algorithms kernel-methods optimization-methods genetic-algorithms evolutionary-strategy quantum-algorithms multiobjective-optimization classifiers quantum-machine-learning supervised-learning-algorithms automatic-machine-learning quantum-inspired-algorithm quantum-kernel
  • Updated Mar 18, 2024
  • Jupyter Notebook

jim-spyropoulos / Trajectory-Analysis-and-Classification-in-Python-Pandas-and-Scikit-Learn

Star 61

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

python machine-learning random-forest dtw scikit-learn classification logistic-regression similarity-measures trajectory-analysis knn trajectory scikitlearn-machine-learning classifiers
  • Updated Feb 1, 2024
  • Python

sairajindroju / Rain-Prediction-DataAnalytics

Star 1

Analyzed a 23-feature dataset, targeting 'RainTomorrow' for weather insights. Conducted thorough data gathering, preprocessing, and feature selection. Evaluated diverse models (Logistic Regression, Random Forest, Decision Trees, K-means, K-nearest neighbors, Hierarchical clustering) and employed technical metrics for in-depth performance analysis.

python machine-learning pytorch seaborn pyspark matplotlib classifiers sk-learn
  • Updated Oct 10, 2023
  • Jupyter Notebook

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