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Big Data Machine Learning | 大数据机器学习

《大数据机器学习》课程是面向信息学科的高年级本科生或研究生开设的基础理论课,目的是培养学生深入理解大数据机器学习理论基础,牢固掌握大数据机器学习方法,并能够解决实际问题等综合能力。课程的主要内容包括:统计学习基本理论,机器学习基本方法,深度学习理论和方法。

Big Data Machine Learning | 大数据机器学习

There is one session available:

After a course session ends, it will be archived.
Estimated 16 weeks
3–5 hours per week
Self-paced
Progress at your own speed
Free
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About this course

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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

At a glance

What you'll learn

Skip What you'll learn
  1. 大数据机器学习的基本概念
  2. 大数据机器学习的技术以及原理
  3. .机器学习以及深度学习的算法

  4. Basic concepts of Big Data Machine Learning

  5. Principles and techniques of Big Data Machine Learning

  6. Algorithms of machine learning and deep learning

About the instructors

Who can take this course?

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