compares different pretrained object classification with per-layer and per-channel quantization using pytorch
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Updated
Jun 12, 2020 - Python
compares different pretrained object classification with per-layer and per-channel quantization using pytorch
A machine learning project developing classification models to predict COVID-19 diagnosis in paediatric patients.
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.
Model optimization with grid search and k-fold
Classification automatique de biens de consommation (OpenClassrooms | Data Scientist | Projet 6)
Temporal Backtracking and Multistep Delay of Traffic Speed Series Prediction
ai-zipper offers numerous AI model compression methods, also it is easy to embed into your own source code
Optimizing convolution function using ARM's NEON Intrinsics
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.
Minimal Reproducibility Study of (https://arxiv.org/abs/1911.05248). Experiments with Compression of Deep Neural Networks
Demonstrates knowledge distillation for image-based models in Keras.
Code of the ICASSP 2022 paper "Gradient Variance Loss for Structure Enhanced Super-Resolution"
Create a binary classifier that is capable of predicting whether applicants will be successful if funded by Alphabet Soup
DA2Lite is an automated model compression toolkit for PyTorch.
Neural network model implemented with flask and SQL to predict the success status of over 100,000 kickstarter companies.
A curated list of awesome open source tools and commercial products for autoML hyperparameter tuning 🚀
This is an End to End project and Api deployment for Spain electricity shortfall prediction
Implementations of machine learning algorithms from scratch using python and numpy
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