什么是机器学习中的神经网络设计
Neural Network Design in Machine Learning
在本课题中,学生将研究如何将机器学习中的基本概念与原则,深入了解无监督学习和监督学习的区别,设计不同应用场景下的分类和回归模型,巩固学习决策树、分类树、回归树、CART等基础知识,理解神经元网络中各个参数的含义和作用,学习线性回归和逻辑回归算法,应用kNN算法于实际生活情况中。
In this program, students will study how to understand the basic concepts and principles in machine learning, and understand the differences between unsupervised learning and supervised learning, design classification and regression models in different application scenarios, and consolidate learning decision trees, classification trees, and regression. Students are expected to learn basic knowledge such as tree and CART, to understand the meaning and function of each parameter in the neural network, to learn linear regression and logistic regression algorithm, and to apply kNN algorithm in real life situation.
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