air_quality_index_bangalore_-2013-2018

In this project, the goal is, Gathering the previous data of environment conditions and Parts per million data. Train various Machine learning models on the same data set, and choose the best one.

alien_vs_predator_transfer-learning

apple_stock_price_predictions

bg-cnn-for-dc-motor-fdi

BG-CNN: A Hybrid Fault Diagnosis Method for Improved Fault Isolation. This repository presents the BG-CNN method, a novel approach that combines the Bond-Graph technique with Convolutional Neural Networks (CNNs) for efficient fault isolation.

cwru_bearing_fault_classification

dc_motor_simulink

explainabel_ai_predictive_maintainance

In this series, we explore various XAI techniques applied to the Tennessee Eastman Process data.

face_recognition

facial_mask_recognition_using_opencv

fake-news-classification-with-lstm

gear-fault-diagnosis

Binary classification between healthy and faulty gear with broken tooth

house-prices-advanced-regression-techniques

image_captioning_with_deployment

ims-bearing-fault-diagnosis

keggle_titanic_77-percent_accuracy

mohan696matlab

mvtec_anomalydetection

nasa-s-turbo-engine-remaining-useful-life-prediction-using-machine-learning

predicting-heart-stroke_kaggle

process-faut-diagnosis-a-supervised-machine-learning-approach

regression_technique_for_turboengine_rul

solar-panel-ifd

spam_classifier_using-naive-bayes-classifier

ssl_based_hybrid_fdi

tep_anomaly_detection_deployment

test_1

unsupervised-_fault_detection-industrial_process

This repository contains code for analyzing the TEP dataset, which is a public dataset for evaluating fault detection and diagnosis algorithms in industrial systems. The dataset includes measurements from a simulated production line, and faults are introduced at specific times during the production process.