Darth-Kronos

Crop-Yield-Prediction

Machine learning (ML) models were engineered after processing agricultural data and Regression models were deployed to predict the yield of 4 major crops. The developed models were then compared with each other to obtain the best performing model.

Cross-lingual-SER

A cross-lingual SER that can learn language invariant representations without requiring target-language data labels

Image-manipulation-CVAE

Using conditional variational autoencoders to manipulate the images

LLM-Chatbot-AWS

Deploying a LLM agent using AWS SageMaker and AWS Lambda

mlops-101

PIDNet_TensorRT

TensorRT implementation for PIDNet

Spectrum-Sensing

Using signal processing based features to train and validate machine-learning algorithms to improve spectrum sensing and related problems in cognitive radios.

trt-custom-plugins

TensorRT plugins for custom operators

Unsupervised-Domain-Adaptation

Empirical evaluation and analysis of state-of-the-art methods for unsupervised domain adaptation on OFFICE-31 dataset, a benchmark dataset for visual domain adaptation.

YOSO_TensorRT

TensorRT implementation of YOSO

Darth-Kronos/Spectrum-Sensing

Using signal processing based features to train and validate machine-learning algorithms to improve spectrum sensing and related problems in cognitive radios.

Darth-Kronos/PIDNet_TensorRT

TensorRT implementation for PIDNet

Darth-Kronos/Unsupervised-Domain-Adaptation

Empirical evaluation and analysis of state-of-the-art methods for unsupervised domain adaptation on OFFICE-31 dataset, a benchmark dataset for visual domain adaptation.

Darth-Kronos/Image-manipulation-CVAE

Using conditional variational autoencoders to manipulate the images

Darth-Kronos/YOSO_TensorRT

TensorRT implementation of YOSO

Darth-Kronos/trt-custom-plugins

TensorRT plugins for custom operators

Darth-Kronos/Crop-Yield-Prediction

Machine learning (ML) models were engineered after processing agricultural data and Regression models were deployed to predict the yield of 4 major crops. The developed models were then compared with each other to obtain the best performing model.

Darth-Kronos/Cross-lingual-SER

A cross-lingual SER that can learn language invariant representations without requiring target-language data labels

Darth-Kronos/File-Converter

Darth-Kronos/PIDNet

TensorRT implementation for PIDNet

Darth-Kronos/awesome-dynamodb

List of resources for learning about modeling, operating, and using Amazon DynamoDB

Darth-Kronos/aws-serverless-telepresence-robot

Darth-Kronos/Deep-Matrix-Factorization-Recommendation-Systems

Comparison of various deep neural networks for recommendation systems

Darth-Kronos/LLM-Chatbot-AWS

Deploying a LLM agent using AWS SageMaker and AWS Lambda

Darth-Kronos/mlops-101

Darth-Kronos/Sign-Language-Interpreter

Real-time sign language interpretation using CNN

Darth-Kronos/Visualizing-CNN

Visualization technique that gives insight into the function of intermediate feature layers and the operation of a Convolutional Neural Network.

Darth-Kronos/Darth-Kronos

Darth-Kronos/darth-kronos.github.io

Darth-Kronos/Handwritten-Digit-Classifier

Darth-Kronos/Image-Pyramids-Blending

Darth-Kronos/QPong-qiskit

Darth-Kronos/SecureMyVote

Blockchain based election system on Azure

Darth-Kronos/stable-diffusion-tritonserver

Deploy HuggingFace’s Stable Diffusion Pipeline with Triton Inference Server

Darth-Kronos/terrain-identification

Terrain Identification from Time Series Data