Best Practices for Applying Deep Learning to Novel Applications

2017/04/05 by Leslie N. Smith, Smith, Leslie N. · 1 voice
Computer Science · Social Sciences · #Anomaly Detection Techniques and Applications #Software Engineering and Design Patterns #Time Series Analysis and Forecasting #cs.AI #cs.NE #cs.SE

paper · pdf · doi:10.48550/arxiv.1704.01568

openalex publication_date 2017/04/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This report is targeted to groups who are subject matter experts in their application but deep learning novices. It contains practical advice for those interested in testing the use of deep neural networks on applications that are novel for deep learning. We suggest making your project more manageable by dividing it into phases. For each phase this report contains numerous recommendations and insights to assist novice practitioners.

Citations

• Software Engineering at Google
• Domain Adaptation for Visual Applications: A Comprehensive Survey

Discussions

• Best Practices for Applying Deep Learning to Novel Applications [hn, 300 points, 17 comments]

Related

• Deep Learning in the Wild
• Introduction to deep learning
• The Open Science of Deep Learning: Three Case Studies
• Improving the Reproducibility of Deep Learning Software: An Initial Investigation through a Case Study Analysis
• Reusing Deep Learning Models: Challenges and Directions in Software Engineering