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Introduction to Trading, Machine Learning & GCP に戻る

Google Cloud による Introduction to Trading, Machine Learning & GCP の受講者のレビューおよびフィードバック

4.0
460件の評価
130件のレビュー

コースについて

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)....

人気のレビュー

MS

Jan 30, 2020

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.

BA

Mar 16, 2020

Very good course us introduction to Trading, ML models for trading, ML, Neural networks concept and approaches, Google cloud platform.

フィルター:

Introduction to Trading, Machine Learning & GCP: 1 - 25 / 128 レビュー

by Carlo R C

Jan 03, 2020

This course is a pre-sales demo of BigQuery. I thought GCP was partnering with the NY Institute of Finance to create the labs on VMs using GCP (which makes sense), but it turns out that the core information about the introduction to trading and ML is minimal, about 20 minutes of substance per week and the rest of the time is Google advertisement for BigQuery and GCP. The skewed theory from the videos ends up with a Google product guide of a specific, more skewed way of running a feature of a product. I thought this course would give me a proper introduction of ML for trading but instead is more focused on the google ecosystem.

I would not recommend this course unless you want to learn more about Google Cloud Platform, BigQuery, TensorFlow or any other google product. The NY Institute of Finance fails to deliver the theory, it seems like google is telling the instructor what to talk about so google can show and tell about its products.

You are better off buying a good book about ML for trading and read the google documentation about the products they have (if you want to use google), it'll be cheaper and more time effective.

by Ricardo C

Dec 27, 2019

Many very interesting concepts, presented in a VERY superficial way. In the practical part, executing a series of instructions that have not been explained is not a synonym for learning. And if we consider that many errors may happen at every step, and there is no contingency guide, that all is terrible!

by Ruedi G

Dec 25, 2019

This is not a good course: a little bit of everything: Frontal theory lectures without much interaction. Exercises that need more copy paste than they provide leanings and commercials for Google. It seems like the units have been reassembled from other courses.

by Krzysztof P

Dec 25, 2019

This course is very introductory and sometimes sounds more like advertisement of GCP than a lecture. Moreover, probably only 40% of the content is orginal. The rest is taken from other courses (i.e. Serverless Deep Learning with TensorFlow on GCP).

by Gavin H

Jan 15, 2020

Though the introduction said the course would focus on just trading and ML, it really is just a set of disjointed modules, often with nothing to do with trading, with little to keep it together. There is a lot of repetition between modules and they really look like they have just been pulled out of other courses. In the final week, the one video even mentions and exercise that does not exist.

by Laurent P

Dec 26, 2019

I usually like online learning, but this was a very weird course to say the least. It honestly felt very piecemeal, like some leftovers from a bunch of other courses had been thrown together without any second thought. I would have been better off just getting the Jupyter files and search for what was missing (that's what I did, anyway). Oh, but the Google infomercial at the end was totally necessary. Seriously, people...

by Saulo D S e R

Jan 09, 2020

Very few information. Poor practical homeworks. Poor quiz. It seems the course really starts on the second course. The first course doesn't worth the investment. It is more a show off of google products than a real course.

by Himalay O

Dec 30, 2019

The course gave me a basic understanding of few types of models including linear regression, time series and neural networks. A few more offline exercises that we can perform on our own would be a good addition to assert the acquired knowledge even more.

by Yun Z L

Dec 29, 2019

having completed "AI for everyone" and 3 out of 5 for the "deep learning specialization", I found quite a few concepts such as the "short history of ML" quite basic, especially week 4's content which was very basic and not trading related. But overall it was good having a refresher from a different perspective.

On the positive side, as someone who has worked in Quant funds prior to the popularity of ML neural networks, I really enjoyed listening to Jack Farmer's in-depth walkthrough of the ML applications in quant strategies. I'm quite looking forward to the rest of the courses in this specialization and will give this 5 stars despite a few minor glitches which are expected for a new course.

by Carlos F P

Feb 29, 2020

This course is a good initial taste of the topics. These topics could be complex but I believe it handles them adequately for an introductory course. I think the use of GCP shows that packaged solutions are a way to be efficient and move faster in industry.

by Marc A

Dec 26, 2019

Would be nice to have some extra step at the end of the lad to actually build a trading strategy instead of stopping at the fitting of the model

by Gerardo G

Jan 10, 2020

I am a physicist and I find it very basic, It did not provide me with any new knowledge whatsoever even with the little amount of knowledge I had of the subjects.

by Vhui77@gmail.com

Dec 25, 2019

This course makes everything easier. It is structured very user friendly for understanding the forest rather than the trees. I have taken courses in Python, Jupyter Notebook, ARIMA forecasting, Linear regression and other Finance and Probability courses to fully appreciate this course. If you dont have these basic knowledge and if they ask you to code every detail, then it would have been impossible. Good job Google and New York Institue of Finance.

by Gehad W

Jan 03, 2020

Excellent course by Google and NY Institue of Finance. Course is well-structured and provides high quality content with good labs. I much enjoyed Jack Farmer putting Quant strategies in a nice and clear structure while explaining complex topics in an intuitive and simple way. Time series and ARIMA modeling with the related lab is also a very good part. I hope the latest Tensorflow 2.x version will be used in next course.

by DAN T K

Jan 05, 2020

Very nice course to understand liner regression, ARIMA and ML. Also, the practice on GCP with notebook is exciting to me

by Carson R

Jan 02, 2020

Other courses recommended before doing this one! Basics of ML, Basics of the stock market, python and sql

by Diderico v E

Jan 02, 2020

Nice overview of the content. Well-organized and effective.

by Hendrik M P

Dec 20, 2019

Great videos without buffering. Thanks!

by Avinash K

Dec 25, 2019

justifies the course topic.

by Fuh C S

Dec 26, 2019

Great Course. Thanks

by Nelson F

Jan 04, 2020

Fantastic course.

by ASHISH D

Dec 30, 2019

Awesome learning.

by Emre K

Dec 24, 2019

Very helpful.

by Atichat P

Dec 28, 2019

Good

by Meisam M

Dec 24, 2019

some explanation in trading was hard, it was realy good to be able to test google cloud services, but needs more practical examples