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Bewertung und Feedback des Lernenden für Sequences, Time Series and Prediction von

4,454 Bewertungen
704 Bewertungen

Über den Kurs

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction. Finally, you’ll apply everything you’ve learned throughout the Specialization to build a sunspot prediction model using real-world data! The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....



3. Aug. 2019

It was an amazing experience to learn from such great experts in the field and get a complete understanding of all the concepts involved and also get thorough understanding of the programming skills.


6. Juni 2020

I really enjoyed this course, especially because it combines all different components (DNN, CONV-NET, and RNN) together in one application. I look forward to taking more courses from

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601 - 625 von 704 Bewertungen für Sequences, Time Series and Prediction

von David L

2. Apr. 2021

I wish I have a graded coding practice.

von Giri D

13. Dez. 2019

A vast portion covered with few videos.

von Aidin G

4. Nov. 2020

Great course as always! Learned alot!

von Akshay K C

19. Sep. 2020

Assignments should be made compulsary

von Tobias B

25. Juni 2020

Great course, but no graded exercises

von Robert G

11. Dez. 2019

I would like to see forex and stocks.

von Komang A W

13. Apr. 2022

very usefull and easy to understand

von Akim B

19. Apr. 2020

Interesting, however somewhat basic

von Milton H A G

7. Juli 2020

Very pragmatic and hands-on course

von Muhammad R

25. Juli 2020

I miss the graded assignments.

von Ramil A

16. Apr. 2020

Graded exercise would be nice

von Isaac D

22. Juli 2021

No code challenges - 4 stars


8. Sep. 2020

It is wonderful experience

von Shitian S

17. Juni 2020

it's good for beginners.

von JackT T

6. Jan. 2021

Very useful course

von Manish S

21. Juni 2020

Awesome experience

von Naveen

12. Mai 2020

No graded exercise

von Aminata G

16. Juni 2020

C'était géniale!

von Ashwani Y

24. Apr. 2020

it was good

von Vikas C

24. Dez. 2019

Good course

von Yu-Chen L

26. Juni 2020


von Joanna S

21. Juni 2020

I am a software engineer with a good base knowledge of machine learning and neural networks, and I took this course to get more specific knowledge about time series and TensorFlow to help with a project using stock market data. The content of this course is very shallow. I don't feel like I learned much reusable knowledge because much of the course is basically walking through code in Jupyter notebooks. If I wanted to just learn to copy someone else's code, I can do that on my own (for free) reading blog posts or tutorials. Also, quiz questions that ask about function names or names of libraries do not show any understanding of concepts and really just felt like filler because they needed 10 questions but hadn't taught any concepts to ask actual questions about.

I'm giving this 3 stars instead of 1 because maybe the audience is supposed to be students with less knowledge of machine learning or programming, or maybe it just doesn't match my learning style.

von Vincenzo T

15. Nov. 2020

The course in general is good and introduces you to the uses of tensorflow keras API with different cases, but i can't give 5 stars because i think it still lacks on fundamental teaching about tensorflow.

I mean that during the course some tensorflow tools appear out of nothing, mainwhile i think would make a lot of sense to dedicate at least one course's module to introduce tensorflow library itself.

Just an example: during the last week we make an extensive use of tensorflow "Dataset" class to load the data into neural networks, and this tool appears out of nothing, but it seems very important and useful stuff that i think would deserve some introduction and explaining before you use it.

von Jiawei X

11. Jan. 2020

This course is great for introduction. BUT it is still lacking very important background information of the Tensorflow Dataset and how to master it.

It makes sense not to go into too deep on the NN model and their theories but when it comes to practical usage of any machine learning packages, data pipelines play very significant role (count towards 60% - 70% of the codes).

In the course we briefly talk about Dataset and use only a few APIs without explaining why and the logic behind them. And tutorials from tensorflow's officials still lacking useful guidelines when dealing with dataset of multiple dimensions.

von Yemi A

16. Aug. 2019

I found the start of the specialism was very well explained; and as a result now I really understand CNNs (as it is was explained much better than the other courses I’m doing on Udemy and LinkedIn Learning). However I would suggest that Andrew and Laurence revisit the latter part of the course from a learner point of view, looking at the pain points along their journey through Sequences and Predictions. Overall, the structure of the whole specialism can be improved, and I find it not as good as my previous course (Andrew’s Standford University Machine Learning Course which was brilliant)