課程信息
3.6
195 個評分
81 個審閱
100% 在線

100% 在線

立即開始,按照自己的計劃學習。
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可靈活調整截止日期

根據您的日程表重置截止日期。
初級

初級

完成時間(小時)

完成時間大約為21 小時

建議:10 hours/week...
可選語言

英語(English)

字幕:英語(English)
100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
初級

初級

完成時間(小時)

完成時間大約為21 小時

建議:10 hours/week...
可選語言

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 6 小時

Artificial Intelligence & Machine Learning

...
Reading
11 個視頻 (總計 75 分鐘), 4 個閱讀材料, 2 個測驗
Video11 個視頻
Specialization Objectives8分鐘
Specialization Prerequisites7分鐘
Artificial Intelligence and Machine Learning, Part I6分鐘
Artificial Intelligence and Machine Learning, Part II7分鐘
Machine Learning as a Foundation of Artificial Intelligence, Part I5分鐘
Machine Learning as a Foundation of Artificial Intelligence, Part II7分鐘
Machine Learning as a Foundation of Artificial Intelligence, Part III7分鐘
Machine Learning in Finance vs Machine Learning in Tech, Part I6分鐘
Machine Learning in Finance vs Machine Learning in Tech, Part II6分鐘
Machine Learning in Finance vs Machine Learning in Tech, Part III8分鐘
Reading4 個閱讀材料
The Business of Artificial Intelligence30分鐘
How AI and Automation Will Shape Finance in the Future30分鐘
A. Geron, “Hands-On Machine Learning with Scikit-Learn and TensorFlow”, Chapter 130分鐘
Jupyter Notebook FAQ10分鐘
Quiz1 個練習
Module 1 Quiz30分鐘
2
完成時間(小時)
完成時間為 6 小時

Mathematical Foundations of Machine Learning

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Reading
9 個視頻 (總計 78 分鐘), 3 個閱讀材料, 2 個測驗
Video9 個視頻
The No Free Lunch Theorem7分鐘
Overfitting and Model Capacity8分鐘
Linear Regression7分鐘
Regularization, Validation Set, and Hyper-parameters10分鐘
Overview of the Supervised Machine Learning in Finance3分鐘
DataFlow and TensorFlow10分鐘
A First Demo of TensorFlow11分鐘
Linear Regression in TensorFlow10分鐘
Reading3 個閱讀材料
I. Goodfellow, Y. Bengio, A. Courville, “Deep Learning”, Chapters 4.5, 5.1, 5.2, 5.3, 5.4分鐘
Leo Breiman, “Statistical Modeling: The Two Cultures”分鐘
Jupyter Notebook FAQ10分鐘
Quiz1 個練習
Module 2 Quiz15分鐘
3
完成時間(小時)
完成時間為 5 小時

Introduction to Supervised Learning

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Reading
4 個視頻 (總計 43 分鐘), 4 個閱讀材料, 2 個測驗
Video4 個視頻
Gradient Descent Optimization10分鐘
Gradient Descent for Neural Networks12分鐘
Stochastic Gradient Descent8分鐘
Reading4 個閱讀材料
A.Geron, “Hands-On ML”, Chapter 9, Chapter 4 (Gradient Descent)分鐘
E. Fama and K. French, “Size and Book-to-Market Factors in Earnings and Returns”, Journal of Finance, vol. 50, no. 1 (1995), pp. 131-155.15分鐘
J. Piotroski, “Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers”, Journal of Accounting Research, Vol. 38, Supplement: Studies on Accounting Information and the Economics of the Firm (2000), pp. 1-4115分鐘
Jupyter Notebook FAQ10分鐘
Quiz1 個練習
Module 3 Quiz15分鐘
4
完成時間(小時)
完成時間為 7 小時

Supervised Learning in Finance

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Reading
9 個視頻 (總計 66 分鐘), 3 個閱讀材料, 2 個測驗
Video9 個視頻
Fundamental Analysis7分鐘
Machine Learning as Model Estimation8分鐘
Maximum Likelihood Estimation10分鐘
Probabilistic Classification Models6分鐘
Logistic Regression for Modeling Bank Failures, Part I8分鐘
Logistic Regression for Modeling Bank Failures, Part II5分鐘
Logistic Regression for Modeling Bank Failures, Part III8分鐘
Supervised Learning: Conclusion2分鐘
Reading3 個閱讀材料
C. Bishop, “Pattern Recognition and Machine Learning”, Chapters 4.1, 4.2, 4.3分鐘
A. Geron, “Hands-On ML”, Chapters 3, Chapter 4 (Logistic Regression)分鐘
Jupyter Notebook FAQ10分鐘
Quiz1 個練習
Module 4 Quiz21分鐘
3.6
81 個審閱Chevron Right

熱門審閱

創建者 ABMay 28th 2018

Exceptional disposition and lucid explanations! Ideal for a Risk Management professional to sharpen machine learning skills!

創建者 LBAug 19th 2018

Audio could be better. Low recording volume makes it difficult to listen sometimes.

關於 New York University Tandon School of Engineering

Tandon offers comprehensive courses in engineering, applied science and technology. Each course is rooted in a tradition of invention and entrepreneurship....

關於 Machine Learning and Reinforcement Learning in Finance 專項課程

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

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