This repository centralize all resources and examples (such as notebooks) that could be use with the OVHcloud AI Training product
git clone https://github.com/ovh/ai-training-examples.git
cd ai-training-examplesThe tutorials are categorised by product and by task.
We offer examples on how to use AI Notebooks, AI Training and AI Apps. There are many forms: python files, ipython notebooks, Dockerfile, ...
The tutorials structure is as follows:
.
├── apps
│ ├── fastapi
│ │ └── spam-classifier-api
│ ├── flask
│ │ ├── hello-world
│ │ ├── object-detection-yolov5-app
│ │ │ ├── static
│ │ │ └── templates
│ │ └── sentiment-analysis-hugging-face-app
│ │ ├── static
│ │ └── templates
│ ├── getting-started
│ │ └── flask
│ │ └── hello-world-api
│ ├── gradio
│ │ └── sketch-recognition
│ └── streamlit
│ ├── audio-classification-app
│ ├── eda-classification-iris
│ ├── simple-app
│ └── speech-to-text
├── jobs
│ ├── jupyterlab
│ │ └── tensorflow
│ └── weights-and-biases
│ └── audio-classification-models-comparaison
│ ├── data-processing
│ └── models-training
└── notebooks
├── audio
│ └── audio-classification
├── computer-vision
│ ├── image-classification
│ │ └── tensorflow
│ │ ├── resnet50
│ │ ├── tensorboard
│ │ └── weights-and-biases
│ └── object-detection
│ └── miniconda
│ ├── yolov5
│ │ └── weights-and-biases
│ └── yolov7
│ └── images
├── getting-started
│ ├── miniconda
│ │ └── ai-notebooks-introduction
│ ├── pytorch
│ └── tensorflow
└── natural-language-processing
├── speech-to-text
│ └── miniconda
│ ├── advanced
│ │ └── sounds
│ ├── basics
│ │ └── sounds
│ └── compare-models
│ └── sounds
└── text-classification
├── hugging-face
│ └── sentiment-analysis-twitter
│ ├── BARThez
│ ├── BERT
│ └── CamemBERT
└── miniconda
└── spam-classifier- Documentation: https://docs.ovh.com/gb/en/publiccloud/ai/
- Contribute: https://github.com/ovh/ai-training-examples/blob/master/CONTRIBUTING.md
- Report bugs: https://github.com/ovh/ai-training-examples/issues
Copyright 2021 OVH SAS
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.