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Вернуться к Introduction to Trading, Machine Learning & GCP

Отзывы учащихся о курсе Introduction to Trading, Machine Learning & GCP от партнера Google Cloud

4.0
звезд
Оценки: 730

О курсе

In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....

Лучшие рецензии

MS

29 янв. 2020 г.

Excellent! But, I am missing some of the prerequisites since I just wanted to take a chance and try things out, but feel like proceeding further might lead to some stumbling blocks.

AJ

20 нояб. 2020 г.

I thought this was excellent. Some familiarity with standard SQL is needed to get the most benefit from the materials, and the course is clearly aimed at GCP users.

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126–150 из 198 отзывов о курсе Introduction to Trading, Machine Learning & GCP

автор: domenico r

13 апр. 2020 г.

автор: Robin L

21 дек. 2020 г.

автор: Wolfgang B

4 мая 2020 г.

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17 июля 2021 г.

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29 мая 2020 г.

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10 янв. 2020 г.

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17 апр. 2020 г.

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2 мар. 2020 г.

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15 апр. 2020 г.

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16 февр. 2020 г.

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16 авг. 2020 г.

автор: Nikolas M

13 янв. 2020 г.

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27 июля 2020 г.

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2 июня 2020 г.

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1 сент. 2020 г.

автор: Andreas W

26 сент. 2020 г.