#c_lang #convolutional_neural_network #convolutional_neural_networks #cpu #inference #inference_optimization #matrix_multiplication #mobile_inference #multithreading #neural_network #neural_networks #simd
https://github.com/google/XNNPACK
https://github.com/google/XNNPACK
GitHub
GitHub - google/XNNPACK: High-efficiency floating-point neural network inference operators for mobile, server, and Web
High-efficiency floating-point neural network inference operators for mobile, server, and Web - google/XNNPACK
#jupyter_notebook #artificial_intelligence #azure #computer_vision #convolutional_neural_networks #data_science #deep_learning #image_classification #image_processing #jupyter_notebook #kubernetes #machine_learning #microsoft #object_detection #operationalization #python #similarity #tutorial
https://github.com/microsoft/computervision-recipes
https://github.com/microsoft/computervision-recipes
GitHub
GitHub - microsoft/computervision-recipes: Best Practices, code samples, and documentation for Computer Vision.
Best Practices, code samples, and documentation for Computer Vision. - microsoft/computervision-recipes
#python #convolutional_neural_networks #cvpr #cvpr2020 #efficient_inference #fbnet #imagenet #mobilenet #mobilenetv3 #model_compression #tensorflow
https://github.com/huawei-noah/ghostnet
https://github.com/huawei-noah/ghostnet
GitHub
GitHub - huawei-noah/Efficient-AI-Backbones: Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's…
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab. - huawei-noah/Efficient-AI-Backbones
#python #convolutional_neural_networks #deep_learning #imagenet #jax #pytorch #tensorflow2 #transfer_learning
https://github.com/google-research/big_transfer
https://github.com/google-research/big_transfer
GitHub
GitHub - google-research/big_transfer: Official repository for the "Big Transfer (BiT): General Visual Representation Learning"…
Official repository for the "Big Transfer (BiT): General Visual Representation Learning" paper. - google-research/big_transfer
#other #artificial_intelligence #autograd #bayesian_statistics #convolutional_neural_networks #data_science #deep_learning #ensemble_learning #feature_extraction #graduate_school #information_theory #interview_preparation #jax #jobs #logistic_regression #loss_functions #machine_learning #python #pytorch #pytorch_tutorial
https://github.com/BoltzmannEntropy/interviews.ai
https://github.com/BoltzmannEntropy/interviews.ai
GitHub
GitHub - BoltzmannEntropy/interviews.ai: It is my belief that you, the postgraduate students and job-seekers for whom the book…
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced research...
#other #classification #convolutional_neural_networks #dataset #datasets #deep_learning #deep_neural_networks #image_classification #keras #machine_learning #python #pytorch #remote_sensing #satellite_data #satellite_imagery #satellite_images #sentinel #tensorflow
https://github.com/robmarkcole/satellite-image-deep-learning
https://github.com/robmarkcole/satellite-image-deep-learning
GitHub
GitHub - satellite-image-deep-learning/techniques: Techniques for deep learning with satellite & aerial imagery
Techniques for deep learning with satellite & aerial imagery - satellite-image-deep-learning/techniques
#c_lang #convolutional_neural_network #convolutional_neural_networks #cpu #inference #inference_optimization #matrix_multiplication #mobile_inference #multithreading #neural_network #neural_networks #simd
XNNPACK is a powerful tool that helps make neural networks run faster on various devices like smartphones, computers, and Raspberry Pi boards. It supports many different types of processors and operating systems, making it very versatile. XNNPACK doesn't work directly with users but instead helps other machine learning frameworks like TensorFlow Lite, PyTorch, and ONNX Runtime to perform better. This means your apps and programs that use these frameworks can run neural networks more quickly and efficiently, which is beneficial because it saves time and improves performance.
https://github.com/google/XNNPACK
XNNPACK is a powerful tool that helps make neural networks run faster on various devices like smartphones, computers, and Raspberry Pi boards. It supports many different types of processors and operating systems, making it very versatile. XNNPACK doesn't work directly with users but instead helps other machine learning frameworks like TensorFlow Lite, PyTorch, and ONNX Runtime to perform better. This means your apps and programs that use these frameworks can run neural networks more quickly and efficiently, which is beneficial because it saves time and improves performance.
https://github.com/google/XNNPACK
GitHub
GitHub - google/XNNPACK: High-efficiency floating-point neural network inference operators for mobile, server, and Web
High-efficiency floating-point neural network inference operators for mobile, server, and Web - google/XNNPACK