论文标题
统计物理XIV的基本问题：机器学习讲座
Fundamental problems in statistical physics XIV: Lecture on Machine Learning
论文作者
论文摘要
机器学习的最新进展为学习算法的实际应用打开了大门，也可以直接在机器学习领域以及与其他学科的边缘进行新的研究方向。感兴趣的情况是与物理学，更具体地说是统计物理学的界面。在此简短的讲座中，我将首先尝试从神经网络的角度简要介绍机器学习。在快速解释了培训程序的一些基本模型和全球方面之后，我将讨论更多详细信息两个示例，说明了从统计物理学的角度可以做什么。
The recent progresses in Machine Learning opened the door to actual applications of learning algorithms but also to new research directions both in the field of Machine Learning directly and, at the edges with other disciplines. The case that interests us is the interface with physics, and more specifically Statistical Physics. In this short lecture, I will try to present first a brief introduction to Machine Learning from the angle of neural networks. After explaining quickly some fundamental models and global aspects of the training procedure, I will discuss into more detail two examples illustrate what can be done from the Statistical Physics perspective.
