Skip to main content

ConvNet architectures on Google-Colaboratory

Project description

Main idea of QuickCNN is to train deep ConvNet without diving into architectural details. QuickCNN works as an interactive tool for transfer learning, finetuning, and scratch training with custom datasets. It has pretrained model zoo and also works with your custom keras model architecture.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

quickcnn-0.0.12.tar.gz (27.1 kB view hashes)

Uploaded source

Built Distribution

quickcnn-0.0.12-py3-none-any.whl (26.0 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page