官术网_书友最值得收藏!

Introduction to Meta Learning

Meta learning is one of the most promising and trending research areas in the field of artificial intelligence right now. It is believed to be a stepping stone for attaining Artificial General Intelligence (AGI). In this chapter, we will learn about what meta learning is and why meta learning is the most exhilarating research in artificial intelligence right now. We will understand what is few-shot, one-shot, and zero-shot learning and how it is used in meta learning. We will also learn about different types of meta learning techniques. We will then explore the concept of learning to learn gradient descent by gradient descent where we understand how we can learn the gradient descent optimization using the meta learner. Going ahead, we will also learn about optimization as a model for few-shot learning where we will see how we can use meta learner as an optimization algorithm in the few-shot learning setting.

In this chapter, you will learn about the following:

  • Meta learning
  • Meta learning and few-shot
  • Types of meta learning
  • Learning to learn gradient descent by gradient descent
  • Optimization as a model for few-shot learning
主站蜘蛛池模板: 丁青县| 霍城县| 西华县| 上犹县| 波密县| 安福县| 南川市| 密云县| 大竹县| 永吉县| 安泽县| 大名县| 通榆县| 保康县| 罗源县| 繁昌县| 阿尔山市| 凯里市| 贵州省| 梨树县| 峡江县| 象州县| 资兴市| 缙云县| 织金县| 锡林郭勒盟| 嘉定区| 祁阳县| 平谷区| 昌都县| 天长市| 榕江县| 昂仁县| 贵德县| 丹寨县| 随州市| 治多县| 贺兰县| 定远县| 新密市| 宜春市|