model-optimization
There are 74 repositories under model-optimization topic.
HanXinzi-AI/awesome-computer-vision-resources
a collection of computer vision projects&tools. 计算机视觉方向项目和工具集合。
sayakpaul/Adventures-in-TensorFlow-Lite
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
sayakpaul/Knowledge-Distillation-in-Keras
Demonstrates knowledge distillation for image-based models in Keras.
sayakpaul/E2E-Object-Detection-in-TFLite
This repository shows how to train a custom detection model with the TFOD API, optimize it with TFLite, and perform inference with the optimized model.
lusinlu/gradient-variance-loss
Code of the ICASSP 2022 paper "Gradient Variance Loss for Structure Enhanced Super-Resolution"
AliAmini93/Telecom-Churn-Analysis
Developed a churn prediction model using XGBoost, with comprehensive data preprocessing and hyperparameter tuning. Applied SHAP for feature importance analysis, leading to actionable business insights for targeted customer retention.
MaitreChen/openvino-lenet-sample
本仓库包含了完整的深度学习应用开发流程，以经典的手写字符识别为例，基于LeNet网络构建。推理部分使用torch、onnxruntime以及openvino框架💖
sub1120/PSR-KD
Automated Shorthand Recognition using Optimized DNNs
bnabis93/vision-language-examples
Vision-lanugage model example code.
da2so/DA2Lite
DA2Lite is an automated model compression toolkit for PyTorch.
lattice-ai/Compressed-DNNs-Forget
Minimal Reproducibility Study of (https://arxiv.org/abs/1911.05248). Experiments with Compression of Deep Neural Networks
MrinmoiHossain/Udacity-Intel-Edge-AI-for-IoT-Developers-Nanodegree
Leverage the Intel® Distribution of OpenVINO™ Toolkit to fast-track development of high-performance computer vision and deep learning inference applications, and run pre-trained deep learning models for computer vision on-premise.
TCLResearchEurope/ptdeco
ptdeco is a library for model optimization by matrix decomposition built on top of PyTorch
K0mp0t/DNN_Model_optimization
Some DNN model optimization experiments and notebooks
awesome-mlops/awesome-hyperparameter-optimization
A curated list of awesome open source tools and commercial products for autoML hyperparameter tuning 🚀
Midhilesh29/PostTrainingQuantization
compares different pretrained object classification with per-layer and per-channel quantization using pytorch
Nizarassad/Guns-Knifes-detection
This project uses YOLOv5 architecture for creating guns and knifes real time detection
SayamAlt/Bank-Customer-Segmentation
Successfully established a clustering model which can categorize the customers of a renowned Indian bank into several distinct groups, based on their behavior patterns and demographic details.
yester31/Quantization_EX
quantization example for pqt & qat
AntonioLunardi/Loan-Classification-Prediction-Competition-Case
Determing the eligibility for granting home loan. ML classification models are used, in order to predict if loans are apporoved or not, based on customers's data.
basiralab/CQSIGN
Affordable GNN using Topological Contraction
fabprezja/Deep-Learning-TPBook-Points
Some Key Points from the Deep Learning Tuning Playbook
yihong1120/Vitis-AI-YOLOv3-TF2-Quantization-Evaluation
"Vitis-AI-YOLOv3-TF2-Quantization-Evaluation" Repo for quantization of YOLOv3 on Vitis-AI using TF2, aimed to deploy model on edge devices with limited resources. Includes training & quantization scripts and evaluation metrics. Experiment with different configurations.
caailab/backtracking
Temporal Backtracking and Multistep Delay of Traffic Speed Series Prediction
cuongvng/Optimizing-Convolution-with-NEON-Intrinsics
Optimizing convolution function using ARM's NEON Intrinsics
emreyesilyurt/model-optimization-kFold-and-grid-search
Model optimization with grid search and k-fold
Jayplect/Funding-recommendation-engine
For this project, I built a binary classifier to predict the success of applicants seeking funding from Alphabet Soup. Leveraging the features in the dataset, the model uses machine learning and neural networks to make accurate predictions.
pgeedh/Hyperparameter-Tuning-with-Keras-Tuner
Practical experience in hyperparameter tuning techniques using the Keras Tuner library. Hyperparameter tuning plays a crucial role in optimizing machine learning models, and this project offers hands-on learning opportunities. Exploring different hyperparameter tuning methods, including random search, grid search, and Bayesian optimization
TanyaChutani/Quantization_Tensorflow
Quantization for Object Detection in Tensorflow 2.x
A82516/AEC
Aprendizagem e Extração de Conhecimento
AliAtaollahi/Dynamic-Deadline-Object-Detection-YOLOv8
A YOLOv8-based object detection system for embedded CPS
Equinox-M/Traffic_Volume_Prediction_Using_TCN
This repository contains code and resources for a project focused on predicting traffic volume using Temporal Convolutional Networks (TCNs). Leveraging the Metro Interstate Traffic Volume dataset from 2012-2018, the project aims to develop an accurate model for short- to medium-term traffic volume forecasting in Minneapolis-St Paul, MN.
JLeigh101/deep-learning-challenge
NU Bootcamp Module 21
ksm26/Quantization-Fundamentals-with-Hugging-Face
Learn linear quantization techniques using the Quanto library and downcasting methods with the Transformers library to compress and optimize generative AI models effectively.
Purushothaman-natarajan/Yoga_Pose-Image-Classification
This repository offers a robust solution for multilabel image classification. Utilizing advanced neural networks like VGG16, VGG19, ResNet50, InceptionV3, DenseNet121, and MobileNetV2, the project achieves precise classification across 107 diverse categories.
WalidKW/Store-Sales-TS-Forecasting
Use machine learning to predict grocery sales