community-code
The Community-code repo includes different kinds of code that helps you integrate with the Peltarion Platform. It can be code for data transforms, calling your model, or just having fun with deep learning.
Tutorial resources
- car_damage_classification - Dataset preprocessing and off-platform evaluation for the tutorial "Classifying car damages".
- denoising_images - Dataset preprocessing and off-platform evaluation for the tutorial "Denoising images".
- fruit_classification - Dataset preprocessing and off-platform evaluation for the tutorial "Classifying fruits".
- movie_review_sentiment - Dataset preprocessing for the tutorial "Movie review sentiment analysis".
- skin_lesion_segmentation - Dataset preprocessing and off-platform evaluation for the tutorial "Skin lesion segmentation".
- tagger-tutorial - Dataset preprocessing and model testing for the tutorial "Predicting mood from raw audio data".
- yeast_dna - Dataset preprocessing and off-platform evaluation for the tutorial "Gene expression prediction".
For more information about the tutorials, see the Knowledge Center tutorials.
Deplyment API examples
- Peltarion_deployment_curl_examples.ipynb - Jupyter Notebook demonstrating use of the deployment API via Curl.
- Peltarion_deployment_JSON_examples.ipynb - Jupyter Notebook demonstrating use of the deployment API with HTTP requests and JSON body content.
- predict_california_house_prices - Model API interface for the tutorial "Predict California house prices".
Note: You may use Sidekick as an easy-to-use anlternative to direct HTTP calls for sending data to your deployed models. For example code, see the tutorial resources, e.g., car_damage_classification, skin_lesion_semgentation, and fruit_classification.
Other resources
- images - Images used in code examples.
- solar_panels - Dataset preprocessing and off-platform analysis for a training example that is related to predictive maintenance of solar panels.
- skin_lesion_classification - Dataset preprocessing and off-platform analysis for a training example that is related to the classification of skin lesions.
Licenses datasets
Datasets provided by Peltarion may be subject to separate third party terms of use or our own license terms. Applicable licenses are listed here: https://peltarion.com/knowledge-center/documentation/terms/dataset-licenses.
Disclaimer
Please note that datasets, machine-learning models, weights, topologies, research papers and other content, including open source software, (collectively referred to as “Content”) provided and/or suggested by Peltarion for use in the Platform and otherwise, may be subject to separate third party terms of use or license terms. You are solely responsible for complying with the applicable terms. Peltarion makes no representations or warranties about Content. You expressly relieve us from any and all liability, loss or risk arising (directly or indirectly) from Your use of any third party content.