课程: AI Data Strategy: Data Procurement and Storage

免费学习该课程！

今天就开通帐号，24,700 门业界名师课程任您挑！

Best practices for sourcing unstructured data

扶贫不能排排坐分果果（话说新农村）

课程: AI Data Strategy: Data Procurement and Storage

开始一个月试用 购买团队方案

Best practices for sourcing unstructured data

“ 百度 此外，恒大农牧官方电商平台恒大优选已经正式上线，消费者通过手机轻松一点，或通过购买精品兑换卡，微信轻松一扫，就可享受到恒大农牧电商平台或卡兑换服务团队送货到家的周到服务。

- [Instructor] In the last video, you saw how to source structured data for ML models, but generative AI brings us into a whole new world, one where we need vast amounts of unstructured data, like text, images, and code. Apart from the sheer volume, the challenge with generative AI is about finding diverse high quality data that you need to help your models learn and consequently generate meaningful content. Teams often think they need to collect every bit of data they can find, but having the biggest data set doesn't guarantee success. It's about having the right kind of data diversity. Think about a large language model like GPT. It's not just trained on perfectly written books and articles. It must also understand how people actually communicate, everything from formal documents to casual conversations, technical manuals to creative writing. This diversity is what allows the model to generate appropriate responses in different contexts. Remember the star framework we discussed…

内容