Big Data Machine Learning | 大数据机器学习

如何处理大数据是机器学习所面临的一个持续性的挑战。目前，机器学习处理大规模数据的问题十分普遍。如何提出一种满足大数据处理需求的机器学习算法是大数据时代的热点研究课题。《大数据机器学习》课程是信息科学系高年级本科生和研究生的一门基础理论课程，其目的是培养学生全面理解大数据机器学习的理论基础，并牢固掌握大数据机器学习的方法以及解决实际问题的能力。本课程主要研究机器学习和深度学习的方法，旨在实现大数据机器学习的应用。本课程主要内容包括：

1. 统计学习的基本理论
2. .机器学习的基本方法
3. 深度学习的理论和方法

An ongoing challenge for machine learning is how to deal with big data. At present, the problem of machine learning dealing with large-scale data is widespread. How to propose a machine learning algorithm to meet the needs of big data processing is a hot research topic in the big data era. The course " Big Data Machine Learning" is a basic theory course for senior undergraduates and postgraduates in information science department. Its purpose is to cultivate students' comprehensive ability to understand the theoretical basis of Big Data Machine Learning, master the methods of Big Data Machine Learning firmly, and solve practical problems. This course focuses on the methodsof machine learning and deep learning, and aims to realize the application of big data machine learning. The main contents of the course include:

1. The basic theories of statistical learning

2. The basic methods of machine learning

3. The theories and methods of deep learning

4. 大数据机器学习的基本概念

5. 大数据机器学习的技术以及原理

6. .机器学习以及深度学习的算法

7. Basic concepts of Big Data Machine Learning

8. Principles and techniques of Big Data Machine Learning

9. Algorithms of machine learning and deep learning