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 deeplearning.ai.
Really like the focus on practical application and demonstrating the latest capability of TensorFlow. As mentioned in the course, it is a great compliment to Andrew Ng's Deep Learning Specialization.
автор: mehryar m•
I'm so glad to take this course and build my knowledge regarding time-series data and modern approaches to create prognostic models. Thanks to Andrew Ng and L. Moroney to provide this course.
автор: SIDDHARTHA P•
Few hands on programming assignments could be better for experience as was the case with starting two courses. Overall good course and the structure was well laid. Thanks for building it up
автор: William G•
Though I feel some aspects of this course did not delve deep enough into the explanations of some functions, the course helped me understand how to use models for time series problems.
автор: winniefred m b•
taking this course was undoubtedly a better idea than endless scans over tensorflow documentation and other books. I am glad I got to do this course, wish I had taken this up earlier
автор: Hyungmin S•
I wish there were more detail explanation about hyper-parameter tuning when we define NN Models.
other than that, this course was great and gave me lot of insights. Thank you.
автор: Yongqing X•
I'd like to learn more about algorithmic principle（Although some Andrew‘s class link is attached. ）why not explain the principle combined with the real example
Wish there were graded programming exercises. The quizzes has questions not relevant to the goal of the lesson ex What is the seasonality of sunspots.
автор: Saikat M•
New techniques were learnt regarding how to create a time-series signal and how they can be manipulated for forcasting and feeding to DNN networks.
автор: Parth A•
A good intro course to time series prediction. Would have loved some more data analysis and other time series methods like ARIMA and seasonal ARIMA
автор: Ruben Y Q•
course is good but it dont get deeper on using things like multivariate time series, in addition the course practice materials where kind of lax
автор: Jessie S•
A little bit too simple cuz it only covers univariate time series practice. Would be better if there's more multivariate time series exercise.
автор: Dan R•
I was really waiting to predict 100 data that was similar to sequence, that being said; this was a good introduction to time series analysis.
автор: Kartik P•
its a nice course but instead of using synthetic data, it would have been better if we use real-time datasets for our practice and learning.
автор: AMAN G•
The programming exercise should not have been optional. But overall, this was an amazing course. A thumbs up from my side. Thanks a lot.
автор: Ruben A M•
A lot of typos and I felt that making the Graded Exercises instead of Non Graded is a much better experience for us the students.
автор: Erik J J D B•
Good and easy to follow course to learn tensorflow. You need a background on Machine Learning to fully benefit from this course.
автор: DING T K•
It is nice in introduction to the use of TF in time series. But a bit difficult in the code which without detail explanation.
автор: Duncan B•
I think this is a helpful introduction. It would have been helpful to delve into some multivariate sequence data examples.
автор: Guillermo B•
It would be great if the projects at the end of each week were graded. They were easily solved using that week lesson.
автор: Thomas B•
This is the best course of the specialization. You learn about applying DNN, RNN, LSTM and CNN to time series data.
автор: Itamar d P R F•
Great Course, enlights you were you should head. Although, it missed some further explanation of the steps used.
автор: Lorenzo N•
Great course! It would have been nice to teach something about multivariate time series forecasting as well
автор: Nikhil K•
Have to complete Andrew Ng's Deeplearning as this is very basic course on top of that for time series data.
автор: Advay M•
add more videos to clear deep understanding of time series and more graded practical assignments too...