Md Junayed Hasan's repositories
Predictive-Maintenance
time-series prediction for predictive maintenance
prognostic_and_rul_prediction_of_bearing_data
One model for RUL and fault prognostic prediction on XJTU bearing dataset
XAI_Notebooks
XAI Notebooks with LIME
dataset
Hosting all datasets collected from various sources
deepJDOT
Implementation of DeepJDOT in Keras
DeepLearningTutorial
Deep Learning tutorial
Domain-Adaptation-Internship
Repository to maintain code for my internship on Domain Adaptation
domain-adaptive-segmentation
Domain adaptation segmentation for volume EM imaging
Event-Identification-Earthquake-Methods
This methods can be used for event identification to detect first arrival time of Vp and Vs. These methods are Akaike Information Criterion, MER and S/L kurt
explainable_artificial_intelligence
Slides, code and resources for model interpretation methods in machine learning and deep learning
FastAI-LIME
FastAI Model Interpretation with LIME
feature-engineering-and-feature-selection
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
gifti
MATLAB GIfTI Library
gradcam_plus_plus-pytorch
A Simple pytorch implementation of GradCAM and GradCAM++
Import-To-Thermal
This repo reads RJPEG dataset and calculate temperature of any given pixel
keras-oneshot
koch et al, Siamese Networks for one-shot learning, (mostly) reimplimented in keras
LIME_classification_explainer
Implementing LIME to explain Naïve Bayes, Random Forest, Logistic Regression, XGBoost, and a Feedforward Neural Network classifiers making binary predictions.
Logo-retrieval
This code is used to extract the ZERNIKE moment and edge gray-level co-occurrence matrix from the images.
projectRUL
to prediction the remain useful life of bearing based on 2012 PHM data
pygsp_tutorial_graphsip
Graph signal processing tutorial, presented at the GraphSiP summer school.
rbm-feature-extraction
Simple Intro to Image Feature Extraction using a Restricted Boltzmann Machine
SHAP-LIME
SHAP and LIME examples
SHAP_tutorial
Tutorial on how to use the SHAP library to explain the feature importance with Shapley values.
Steel-Plates-fault-diagnosis-using-Classification-Models
The objective of the project is to classify steel plates fault into 7 different types. The end goal is to train several machine Learning Algorithms for automatic pattern recognition.
time_series_prediction
Learmin time series forcasting
Turbofan_usefull_life_prediction
given run to failure measurements of various sensors on a sample of similar jet engines, estimate the remaining useful life (RUL) of a new jet engine that has measurements of the same sensor for a period of time equal to its current operational time.