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Learner Reviews & Feedback for Sequences, Time Series and Prediction by DeepLearning.AI

4.7
stars
4,953 ratings

About the Course

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 deeplearning.ai 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....

Top reviews

MI

Jun 6, 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 deeplearning.ai.

JH

Mar 21, 2020

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.

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576 - 600 of 781 Reviews for Sequences, Time Series and Prediction

By Shubham K

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Aug 18, 2020

Really nice introduction time series data analysis for regression and prediction. This course extends what you will learn in the rest of the specialisation (NN, Dense Layers, Convolutions, RNN, LSTM) to univariate time series data. I highly recommend this. Its very easy after you do rest of courses from specialisation. Good luck learning. And kudos to Laurence and Dr Andrew Ng for being a lovely instructors and making this accessible to all .

By 4SF18IS103 - S A

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Jun 7, 2020

I liked the flow of the course, working on synthetic data and then moving to real data. But I also think it would be better if I had already taken Andrew Ng's Deep Learning Course before approaching this Course. Plus since there weren't any Graded Programming exercise, it didn't feel like I would be confident in making my own model. So I'm going back and taking Deep learning course.

By Tibor S

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Jan 3, 2021

Great course for a brief intorduction to time series predictions. One needs to integrate knowledge gained from somewhere else (i.e. the course is not comprehensive, but that is also not expected). What I was missing is clarification from authors of some of the important questions/comments in the forum. Several things from the course are left unexplained. Otherwise, I recommend it!

By Gerard S

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Mar 26, 2020

First of all congratulations on the specialization. I felt that I have improved a lot my previous knowledge of Machine Learning and programming with Python and TS. One improving note:I felt that this course could go to third place in the specialization. You go deeper in CNN and LSTM which I missed in the previous one :)

Also, it would be great 2 examples of real-world scenarios

By Dustin Z

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Jun 27, 2020

Fun course, like the rest in the series. I hadn't seen neural networks applied to time series, so that was really worthwhile to learn.

There are still some rough edges and a few parts of the labs that aren't addressed in the videos.

I really enjoy the format of the courses which emphasized a lot of experimentation with networks and provided opportunity for trial and error.

By Eric L

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Dec 11, 2020

If one has seen LSTMs from the previous course and has been exposed to time series there is a little conceptual material to learn from this course, but of course the focus is on tensorflow/keras programming. Highlights were learning how to include lambda layers (which allow one to execute arbitrary code in the network) and how to automate selection of the learning rate.

By Vladimir K

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Apr 26, 2021

Very nice explanations and videos, so I really like it. Basic for timeseries covered and a lot of detailed explanation provided how to apply TF to forecasting. However, quizes are too trivial and doesn't measure understanding of material IMHO. It will be great if separate data set will be used to control understanding of material and motivate to practice more with TF.

By yuan j

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Aug 16, 2020

I learned some time series models and processing methods, but I think this course is too simple and too shallow, for example, there is no prediction of the situation that contains complex features, and how to combine autoregressive features with other features. Models in this course are very popular and are used by everyone, there is no deep stuff

By Yusuf M

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Jun 13, 2020

A really helpful course for those who have just started their journey in the field of machine learning and AI. Strongly recommended for gaining great insights within the field, though all the materials covered are quiet shallow and practical. Use this as a way of learning the tools, not for mastering the theoretical background behind it.

By Arslan G

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Mar 28, 2021

I really wish you could extend the course to multivariate time series prediction, as well as into multivariate time-series multiclass classification. That was indeed the reason why I wanted to learn more about sequence models, as I will be using them in my research on decoding EEG signal. apart from that, it's an excellent course

By Abhinandan T N

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Apr 26, 2020

Sunspot example was good, but i preferred to have few more examples to exhibit different types of real data, like data having both seasonal and also trend. Though the concept is well explained using synthetic data confidence on the subject would have more if had real data for all different types.

By Amir H

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Dec 14, 2019

Thank you for this very interesting and informative course. I really enjoyed the simplicity in explanation and the hands-on implementations. One thing that I think will improve this course further is to add more intuition and explanation of using particular structures like CNN followed by LSTM.

By Vaibhav v s

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Jul 22, 2020

The awesome learning experience with Coursera. So far, I have completed up to the Deep learning specialization. All the courses are well structured with self-learning, live quiz, and assessment. The trainers are good, connect to students, and answer questions. Happy learning.

By FERNANDO D H S

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Jul 10, 2020

Good course, I'd liked more the evaluation methodology of the first two courses on the specialization: questionare and coding excercises. Although here we have ungraded excercises it is more rewarding to see that effor translated to the grades.

Thanks again and great courses.

By Roghaiyeh S

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Aug 2, 2019

I was looking for a basic step by step guide to Tensorflow and this course was amazing. I can now use my knowledge in DL from Deep Learning course better. The instructor was great, explained everything clearly. I think it was better if there was programming assignments too.

By Sharad C

•

Dec 30, 2020

This course enables you to start using TensorFlow as an off the shelf tool. The idea of this course is to make you comfortable with using TensorFlow for predicting time series data. Theory and statistics behind dealing with such data is beyond the scope of this course.

By Anson L

•

Apr 11, 2023

This is a good summary of all techniques learnt from this specialization, even though the problems are quite beginner level, it give you enough space to practice the foundation of TensorFlow workflow. Great course and its best work with Deep Learning specialization.

By Deleted A

•

Sep 6, 2019

I think this course will be of great help if one has worked on time series data. I was a complete novice to time series, and found it difficult to relate. However, I learnt a great deal about the tensorflow technical aspects.

Thanks Lawrence for making it so easy :)

By Alfonso C

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Sep 20, 2019

The course is great, but I would have loved knowing more about how to deal with multivariate time-series, data sets with many time-series, variable prediction horizon etc.

Hope a more advanced course on time series forecast with tf.keras is under construction! ;-)

By Raphy B

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Apr 30, 2021

The exercises are not so well constructed compared to the other courses in this specialization. Overall, the content is "spot-on" (pun intended) when it comes to explaining time-series and what methods we can use to approach to these problems.

By Yogendra S

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May 25, 2020

It was great to start with synthetic data than applying the model to the actual data. It would have been great if assignments were mandatory and new case studies could be practiced. Otherwise course is great to do hands on with tensorflow.

By David R C S

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Jan 6, 2021

before this course, I didn't have knowledge about time series and the problem with the course is I end with the same lack of knowledge because it's more like a tutorial about how to build your NN that a understanding of what is going on.

By Yingnan X

•

Oct 28, 2019

The homework exercise seems to heavily overlap with the demo notebook that I can simply copy and paste the code into the exercise notebook. It would be great if in the future the exercise can be a little harder and involve more thinking.

By Shiladitya P

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Mar 19, 2020

I learned the best practices for forecasting using statistical techniques as well as deep learning networks in this course. One point for improvement is to focus on a few multi-variate examples with code, which was absent in the course.

By Adnan D

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Dec 7, 2020

It was good totally, but I think the assignments weren't enough also I expected the multivariate time series to be covered but it wasn't, I'm waiting to see this teacher next course soon I wish for better assignments and a cool topic!