Chevron Left
Вернуться к Anomaly Detection in Time Series Data with Keras

Отзывы учащихся о курсе Anomaly Detection in Time Series Data with Keras от партнера Coursera Project Network

4.0
звезд
Оценки: 45
Рецензии: 14

О курсе

In this hands-on introduction to anomaly detection in time series data with Keras, you and I will build an anomaly detection model using deep learning. Specifically, we will be designing and training an LSTM autoencoder using the Keras API with Tensorflow 2 as the backend to detect anomalies (sudden price changes) in the S&P 500 index. We will also create interactive charts and plots using Plotly Python and Seaborn for data visualization and display our results in Jupyter notebooks. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Keras pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Лучшие рецензии

Фильтр по:

1–14 из 14 отзывов о курсе Anomaly Detection in Time Series Data with Keras

автор: Joerg A

May 24, 2020

The quiz has a question about "image anomaly detection" - not fitting the course.

There is little explanation, especially what the influence of the parameters are. Most of the time one spends typing and the aloted rhyme time is way too short. I was watching at 2x speed (an annotation told to use 1.5x speed) AND WAS STILL NOT FINISHED when the allotted time was over.

Think hard if you want to pay money for that stressed learning pace.

автор: Amit D

May 31, 2020

Pathetic experience! I see that this is a good idea executed poorly. Clearly Rhyme is not ready yet. I experienced the following issues. 1. Long connection times for Rhyme. In many cases, the desktop didn't even connect. 2. The keyboard of your machine is not synced with Rhyme's desktop. So, certain keys (e.g. CAPS LOCK) don't work. 3. The instructor doesn't explain why he is doing something, just does it.

Coursera should apologize for wasting my time.

автор: Wim P

May 30, 2020

The above rating has nothing to do with the actual content, but has everything to do with the flawed system used to bring the content.

After trying to start this one hour course for over three hours, I gave up. The product (Rhyme) is clearly not ready, so it's not worth your money (yet?).

If you compare the value you get out of these courses versus the other courses on the platform, this should actually be zero out of five.

автор: swarnima

May 06, 2020

It is one of the best guided project I came through on coursera. The project is of intermediate level, quite clear and understandable. The instructor from rhyme was quite good. He explained every part, every function and reason behind their use quite clearly. I recommend this to anyone who is already into time series forecasting and wants to improve his/her skills into it.

автор: Octavio A T N

Jun 02, 2020

This guide is incredible, easy to understand for beginners in the field like me, I'm really grateful because it helps me a lot.

автор: Jacoby W

May 19, 2020

I love how well he explained everything and made it simple to follow

автор: khushbu G

May 30, 2020

An informative course, worth spending time on!

автор: Rishabh R

May 06, 2020

Excellent project

автор: Dr. H M

May 22, 2020

thank u coursera

автор: XAVIER S M

Jun 02, 2020

Very Helpful !

автор: Reinhold L

May 02, 2020

Useful example

автор: Ashwin P

May 21, 2020

good

автор: hariri y

May 26, 2020

When I was taken this guided project, I was attracted by the title (Anomaly Detection in time series), but when I started the project I was very unsatisfied, I found little bit of explanation about the theory behind each steps of coding (no picture, no schema), without any explanation even for dimension of input and output. and finally I was surprised by the time to work on the cloud is limited, and it got me out the cloud before finishing the code. Doesn't recommend it

автор: Stéphane F

Jun 01, 2020

Litteraly awful. A waste of time when you just copy code without explanation. It's actually worse when you know about what you could do, and you compare it to the level of this project. Also, there's no interpretation of the model's results. When you're done writting the code mindlessly, the project is done.