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Отзывы учащихся о курсе Guided Tour of Machine Learning in Finance от партнера New York University

3.8
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Оценки: 640

О курсе

This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. The goal of Guided Tour of Machine Learning in Finance is to get a sense of what Machine Learning is, what it is for and in how many different financial problems it can be applied to. The course 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 Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course....

Лучшие рецензии

LP

22 окт. 2021 г.

Very useful course. Personally, I think that there should have been more focus on the implementation of tensorflow and neural network codes. Overall the course is well structured and very clear.

KD

23 авг. 2019 г.

Introduction of ML for Financial application with combination of Scikit learn, Statsmodels and Tensorflow with neuralnets made this class very interesting. Learned and Enjoyed lot.

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1–25 из 195 отзывов о курсе Guided Tour of Machine Learning in Finance

автор: Maciej O

6 дек. 2018 г.

автор: Teemu P

24 февр. 2019 г.

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27 янв. 2019 г.

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2 дек. 2018 г.

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24 окт. 2018 г.

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23 апр. 2019 г.

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11 июля 2018 г.

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5 авг. 2018 г.

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3 июня 2019 г.

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16 сент. 2019 г.

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21 мая 2020 г.

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3 дек. 2019 г.

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23 окт. 2021 г.

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28 февр. 2020 г.

автор: Walter O A

5 янв. 2019 г.

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25 авг. 2018 г.

автор: Mayank J

17 нояб. 2019 г.