Towards A Visual Programming Tool to Create Deep Learning Models

• URL: http://arxiv.org/abs/2303.12821v1
• Date: Wed, 22 Mar 2023 16:47:48 GMT
• Title: Towards A Visual Programming Tool to Create Deep Learning Models
• Authors: Tommaso Cal\`o and Luigi De Russis
• Abstract summary: DeepBlocks is a visual programming tool that allows Deep Learning developers to design, train, and evaluate models without relying on specific programming languages. We derived design goals from a 5-participants formative interview, and we validated the first implementation of the tool through a typical use case.
• Score: 15.838427479984926
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Deep Learning (DL) developers come from different backgrounds, e.g., medicine, genomics, finance, and computer science. To create a DL model, they must learn and use high-level programming languages (e.g., Python), thus needing to handle related setups and solve programming errors. This paper presents DeepBlocks, a visual programming tool that allows DL developers to design, train, and evaluate models without relying on specific programming languages. DeepBlocks works by building on the typical model structure: a sequence of learnable functions whose arrangement defines the specific characteristics of the model. We derived DeepBlocks' design goals from a 5-participants formative interview, and we validated the first implementation of the tool through a typical use case. Results are promising and show that developers could visually design complex DL architectures.

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