ajayarunachalam/Multi-Spectral-Imaging-RaspberryPi-Design

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Updated almost 3 years ago

ajayarunachalam/Multi-Spectral-Imaging-RaspberryPi-Design

ajayarunachalam

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Low-Cost, Portable, and Plug-and-Play Multi-Spectral Prototype Design

Deep_XF

Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.

Jupyter Notebook

msda

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

Jupyter Notebook

pynmsnn

NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch

Jupyter Notebook

Neighbor-Discovery

P2P Network Resource Discovery Simulation in MANET

EDA

Exploratory Data Analysis

Jupyter Notebook

vision-transformer-demo

Designing, Implementing & Deploying Transformer Deep Learning Network Architecture for computer vision tasks

Jupyter Notebook

RegressorMetricGraphPlot

Python package to simplify plotting of common evaluation metrics for regression models. Metrics included are pearson correlation coefficient (r), coefficient of determination (r-squared), mean squared error (mse), root mean squared error(rmse), root mean squared relative error (rmsre), mean absolute error (mae), mean absolute percentage error (mape), etc.

Jupyter Notebook

pychatgpt_gui

A simple, ease-to-use python APP built for unleashing the power of GPT with custom-data and pre-trained inferences.

nlp_demo

Predicting next set of words with BERT, GPT, and XLNET

meta-self-learner

Meta Ensemble Self-Learning Model with Optimization

Jupyter Notebook