Chevron Left
Back to Sequences, Time Series and Prediction

Learner Reviews & Feedback for Sequences, Time Series and Prediction by deeplearning.ai

4.6
stars
1,125 ratings
175 reviews

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

OR

Aug 04, 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.

VV

Nov 26, 2019

Great course! The notebooks were a great help for understanding the material. I only wish there were auto-graded notebooks in addition to the quizzes like in some of the other courses by Andrew Ng.

Filter by:

101 - 125 of 175 Reviews for Sequences, Time Series and Prediction

By Sergei A

Jul 31, 2019

Thank you guys for this course!

By Matteo

Oct 11, 2019

Interesting and usefull

By Munimahesh B

Aug 18, 2019

It gave nice hands on

By Mani S

Dec 26, 2019

Nice and easy paced.

By Oleksandr M

Aug 14, 2019

Very useful. Thanks!

By Barclay B

Jan 19, 2020

Excellent course!

By Yergali B

Oct 06, 2019

Finally! We did!

By Pachi C

Sep 20, 2019

Fantastic course

By Marco A P N

Sep 24, 2019

It's very great

By Mats E

Aug 16, 2019

Awesome course.

By Anoushkrit G

Nov 26, 2019

Great course!!

By Ravi

Oct 11, 2019

Great course.

By ZefengYu

Aug 27, 2019

非常棒的课程,内容很新颖

By Mohammad Z

Jan 23, 2020

Really Nice

By Samarjeet S

Dec 19, 2019

Good course

By Efstathios C

Jan 05, 2020

Thank you!

By rudraps

Sep 09, 2019

Thank You.

By sheetal

Jan 11, 2020

Worth it.

By Puran Z

Nov 17, 2019

Excellent

By Rodrigo R N

Sep 24, 2019

Show!

By 李英斌

Sep 18, 2019

nice!

By Jurassic

Sep 06, 2019

good

By echo

Aug 31, 2019

good

By 林韋銘

Sep 11, 2019

gj

By Egor E

Aug 24, 2019

I like very match the first and second week of the course, because it contains dense new theoretical and practical things. The idea of time series forecasting and preparing windowed dataset was explained very clear and was very usefull for all next lessons. Also the difference between statistic and neural network approaches was very helpful.

The 3 and 4 week I would prefer zip in one , because the experiments with RNN, LSTM and Conv is very familiar and actually I've done them together one by one. I would pleased to learn some explanation and examples why each type of architecture follow their result. How the results depend on dataset preparation. Particulary, I did not get what architecture work better with seasonality, autocorrelations, and noise.