Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

Last update: Dec 31, 2022

Overview

Google Cloud Vertex AI Samples

Welcome to the Google Cloud Vertex AI sample repository.

Overview

The repository contains notebooks and community content that demonstrate how to develop and manage ML workflows using Google Cloud Vertex AI.

Repository structure

├── community-content - Sample code and tutorials contributed by the community
├── notebooks
│   ├── community - Notebooks contributed by the community
│   ├── official - Notebooks demonstrating use of each Vertex AI service
│   │   ├── automl
│   │   ├── custom
│   │   ├── ...

Contributing

Contributions welcome! See the Contributing Guide.

Getting help

Please use the issues page to provide feedback or submit a bug report.

Disclaimer

This is not an officially supported Google product. The code in this repository is for demonstrative purposes only.

Feedback

Please feel free to fill out our survey to give us feedback on the repo and its content.

Owner

Google Cloud Platform

GitHub Repository https://cloud.google.com/vertex-ai

Transformer based SAR image despeckling

Transformer based SAR image despeckling Using the code: The code is stable while using Python 3.6.13, CUDA =10.1 Clone this repository: git clone htt

27 Nov 13, 2022

TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"

Simulated+Unsupervised (S+U) Learning in TensorFlow TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial T

569 Dec 29, 2022

Official implementation of our paper "Learning to Bootstrap for Combating Label Noise"

Learning to Bootstrap for Combating Label Noise This repo is the official implementation of our paper "Learning to Bootstrap for Combating Label Noise

21 Apr 09, 2022

Neurolab is a simple and powerful Neural Network Library for Python

Neurolab Neurolab is a simple and powerful Neural Network Library for Python. Contains based neural networks, train algorithms and flexible framework

152 Dec 06, 2022

Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

(ACMMM 2021 Oral) SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment This repository shows two tasks: Face landmark detection and Fac

51 Dec 13, 2022

Supporting code for the Neograd algorithm

Neograd This repo supports the paper Neograd: Gradient Descent with a Near-Ideal Learning Rate, which introduces the algorithm "Neograd". The paper an

12 May 01, 2022

Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples

Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples This repository is the official implementation of paper [Qimera: Data-free Q

21 Nov 03, 2022

An NLP library with Awesome pre-trained Transformer models and easy-to-use interface, supporting wide-range of NLP tasks from research to industrial applications.

简体中文 | English News [2021-10-12] PaddleNLP 2.1版本已发布！新增开箱即用的NLP任务能力、Prompt Tuning应用示例与生成任务的高性能推理！ 🎉 更多详细升级信息请查看Release Note。 [2021-08-22]《千言：面向事实一致性的生

6.9k Jan 01, 2023

Unofficial implementation of Proxy Anchor Loss for Deep Metric Learning

Proxy Anchor Loss for Deep Metric Learning Unofficial pytorch, tensorflow and mxnet implementations of Proxy Anchor Loss for Deep Metric Learning. Not

3 Jun 09, 2021

A-ESRGAN aims to provide better super-resolution images by using multi-scale attention U-net discriminators.

A-ESRGAN: Training Real-World Blind Super-Resolution with Attention-based U-net Discriminators The authors are hidden for the purpose of double blind

77 Dec 16, 2022

I tried to apply the CAM algorithm to YOLOv4 and it worked.

YOLOV4：You Only Look Once目标检测模型在pytorch当中的实现 2021年2月7日更新：加入letterbox_image的选项，关闭letterbox_image后网络的map得到大幅度提升。目录性能情况 Performance 实现的内容 Achievement

55 Dec 05, 2022

We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University

213 Dec 27, 2022

Official Pytorch Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images.

IAug_CDNet Official Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images. Overview We propose a

53 Dec 02, 2022

Pytorch implementation of Deep Recursive Residual Network for Super Resolution (DRRN)

DRRN-pytorch This is an unofficial implementation of "Deep Recursive Residual Network for Super Resolution (DRRN)", CVPR 2017 in Pytorch. [Paper] You

192 Dec 12, 2022

ERISHA is a mulitilingual multispeaker expressive speech synthesis framework. It can transfer the expressivity to the speaker's voice for which no expressive speech corpus is available.

ERISHA: Multilingual Multispeaker Expressive Text-to-Speech Library ERISHA is a multilingual multispeaker expressive speech synthesis framework. It ca

43 Nov 27, 2022

Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

Related tags

Overview

Google Cloud Vertex AI Samples

Overview

Repository structure

Contributing

Getting help

Disclaimer

Feedback

Owner

Google Cloud Platform

Transformer based SAR image despeckling

TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"

Official implementation of our paper "Learning to Bootstrap for Combating Label Noise"

Neurolab is a simple and powerful Neural Network Library for Python

Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

Supporting code for the Neograd algorithm

Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples

An NLP library with Awesome pre-trained Transformer models and easy-to-use interface, supporting wide-range of NLP tasks from research to industrial applications.

Unofficial implementation of Proxy Anchor Loss for Deep Metric Learning

A-ESRGAN aims to provide better super-resolution images by using multi-scale attention U-net discriminators.

I tried to apply the CAM algorithm to YOLOv4 and it worked.

We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

Official Pytorch Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images.

Pytorch implementation of Deep Recursive Residual Network for Super Resolution (DRRN)

ERISHA is a mulitilingual multispeaker expressive speech synthesis framework. It can transfer the expressivity to the speaker's voice for which no expressive speech corpus is available.

Sharing of contents on mitochondrial encounter networks

Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)

Code accompanying paper: Meta-Learning to Improve Pre-Training

EDPN: Enhanced Deep Pyramid Network for Blurry Image Restoration

HGCAE Pytorch implementation. CVPR2021 accepted.