课程信息

18,560 次近期查看

学生职业成果

20%

完成这些课程后已开始新的职业生涯

18%

通过此课程获得实实在在的工作福利
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为18 小时
英语(English)
字幕:英语(English)

学生职业成果

20%

完成这些课程后已开始新的职业生涯

18%

通过此课程获得实实在在的工作福利
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为18 小时
英语(English)
字幕:英语(English)

讲师

提供方

New York University 徽标

New York University

教学大纲 - 您将从这门课程中学到什么

1

1

完成时间为 5 小时

Fundamentals of Supervised Learning in Finance

完成时间为 5 小时
9 个视频 (总计 71 分钟), 4 个阅读材料, 1 个测验
9 个视频
Introduction to Fundamentals of Machine Learning in Finance4分钟
Support Vector Machines, Part 18分钟
Support Vector Machines, Part 27分钟
SVM. The Kernel Trick8分钟
Example: SVM for Prediction of Credit Spreads9分钟
Tree Methods. CART Trees9分钟
Tree Methods: Random Forests8分钟
Tree Methods: Boosting9分钟
4 个阅读材料
A. Smola and B. Scholkopf, “A Tutorial on Support Vector Regression”, Statistics and Computing, vol. 14, pp. 199-229, 200415分钟
A. Geron, “Hands-On Machine Learning with Scikit-Learn and TensorFlow”, Chapters 6 & 730分钟
K. Murphy, “Machine Learning: A Probabilistic Perspective”, MIT Press, 2009, Chapter 16.415分钟
Jupyter Notebook FAQ10分钟
2

2

完成时间为 4 小时

Core Concepts of Unsupervised Learning, PCA & Dimensionality Reduction

完成时间为 4 小时
6 个视频 (总计 54 分钟), 3 个阅读材料, 1 个测验
6 个视频
PCA for Stock Returns, Part 14分钟
PCA for Stock Returns, Part 29分钟
Dimension Reduction with PCA9分钟
Dimension Reduction with tSNE11分钟
Dimension Reduction with Autoencoders9分钟
3 个阅读材料
C. Bishop, “Pattern Recognition and Machine Learning”, Chapter 12.115分钟
A. Geron, “Hands-On ML”, Chapters 8 & 1530分钟
Jupyter Notebook FAQ10分钟
3

3

完成时间为 4 小时

Data Visualization & Clustering

完成时间为 4 小时
7 个视频 (总计 50 分钟), 3 个阅读材料, 1 个测验
7 个视频
UL. K-clustering8分钟
UL. K-means Neural Algorithm7分钟
UL. Hierarchical Clustering Algorithms10分钟
UL. Clustering and Estimation of Equity Correlation Matrix5分钟
UL. Minimum Spanning Trees, Kruskal Algorithm6分钟
UL. Probabilistic Clustering6分钟
3 个阅读材料
C. Bishop, “Pattern Recognition and Machine Learning”, Clustering and EM: Chapter 930分钟
G. Bonanno et. al. “Networks of equities in financial markets”, The European Physical Journal B, vol. 38, issue 2, pp. 363-371 (2004)15分钟
Jupyter Notebook FAQ10分钟
4

4

完成时间为 5 小时

Sequence Modeling and Reinforcement Learning

完成时间为 5 小时
11 个视频 (总计 101 分钟), 3 个阅读材料, 1 个测验
11 个视频
Sequence Modeling10分钟
SM. Latent Variables for Sequences8分钟
SM. State-Space Models9分钟
SM. Hidden Markov Models9分钟
Neural Architecture for Sequential Data12分钟
RL. Introduction8分钟
RL. Core Ideas7分钟
Markov Decision Process and RL8分钟
RL. Bellman Equation6分钟
RL and Inverse Reinforcement Learning11分钟
3 个阅读材料
C. Bishop, “Pattern Recognition and Machine Learning”, Chapter 1310分钟
S. Marsland, “Machine Learning: an Algorithmic Perspective” (Chapman & Hall 2009), Chapter 1315分钟
Jupyter Notebook FAQ10分钟

审阅

来自FUNDAMENTALS OF MACHINE LEARNING IN FINANCE的热门评论

查看所有评论

关于 Machine Learning and Reinforcement Learning in Finance 专项课程

The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance. The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) mapping the problem on a general landscape of available ML methods, (2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and (3) successfully implementing a solution, and assessing its performance. The specialization is designed for three categories of students: · Practitioners working at financial institutions such as banks, asset management firms or hedge funds · Individuals interested in applications of ML for personal day trading · Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance. The modules can also be taken individually to improve relevant skills in a particular area of applications of ML to finance....
Machine Learning and Reinforcement Learning in Finance

常见问题

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • 您注册课程后,将有权访问专项课程中的所有课程,并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

  • 如果订阅,您可以获得 7 天免费试听,在此期间,您可以取消课程,无需支付任何罚金。在此之后,我们不会退款,但您可以随时取消订阅。请阅读我们完整的退款政策

  • 是的,Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请,申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤,包括毕业项目。了解更多

还有其他问题吗?请访问 学生帮助中心