Collecting and Annotating Data for AI with Kiran Vajapey - TWiML Talk #130
Published:Apr 23, 2018 17:36
•1 min read
•Practical AI
Analysis
This article summarizes a podcast episode featuring Kiran Vajapey, a human-computer interaction developer. The discussion centers on data collection and annotation techniques for AI, including data augmentation, domain adaptation, and active/transfer learning. The interview highlights the importance of enriching training datasets and mentions the use of public datasets like Imagenet. The article also promotes upcoming events where Vajapey will be speaking, indicating a focus on practical applications and real-world AI development. The content is geared towards AI practitioners and those interested in data-centric AI.
Key Takeaways
- •The interview focuses on data collection and annotation techniques for AI.
- •It highlights the use of data augmentation, domain adaptation, and active/transfer learning.
- •The article promotes upcoming events related to AI and data science.
Reference
“We explore techniques like data augmentation, domain adaptation, and active and transfer learning for enhancing and enriching training datasets.”