创意人工智能与机器学习数据集
我刚刚读到一些项目是如何利用亚马逊评论来训练人工智能和机器学习进行情感分析的。<p>每条亚马逊评论都必须附带星级评分。如果星级评分较低，那么附带的文本很可能是负面的，反之亦然。<p>这让我大开眼界。<p>这种方法完全自给自足。无需雇佣肯尼亚或印度的人来对一段文本进行评分，以确定和标记其情感。<p>我认为这是一个非常有创意的方式来解决“数据问题”。<p>我想了解更多关于这种创意解决方案的信息。<p>请在这个页面上分享你所知道的关于这种创意解决方案（或你对“数据问题”的创意解决方案的想法），以便我们可以有一个参考资源。<p>谢谢。
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I just read about how, to train AIML to do sentiment analysis, some projects use Amazon reviews for data.<p>See, every Amazon review has to be accompanied by a star rating. if the star rating is poor, then the accompanying text is likely to be negative. And vice versa.<p>Blew my mind.<p>It's totally self-contained. No need to hire humans in Kenya or India to rate a piece of text to determine and label its sentiment.<p>I thought this was a highly creative way to approach the "data problem".<p>I want to learn more about such creative solutions to the "data problem".<p>Please share what you know about such creative solutions (or your ideas on creative solutions to the "data problem") on this page so we can have a resource to reference.<p>Thank you.