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Avis et commentaires pour d'étudiants pour Sequences, Time Series and Prediction par

4,691 évaluations

À propos du cours

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....

Meilleurs avis


21 mars 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.


6 juin 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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276 - 300 sur 743 Avis pour Sequences, Time Series and Prediction

par Balaji T

29 oct. 2022

Excellent course for learning Timeseries based forecasting in general.

par Alan F T

10 oct. 2020

Excellent course with real practical examples and great walk throughs.

par Mostafa G

5 août 2019

Excellent course to take after completing Deep Learning Specialization

par Fabiana C R

13 févr. 2021

Good course. I just wished they would cover multivariate time series.

par Thar H S

18 juin 2020

It really simple and useful for my career. Thank you for teaching me.

par Abhiram V

1 mars 2020

The content and visualization helps to understand the problem so well

par Jeferson F

10 sept. 2019

Very good course! I liked it very much! Thanks for all this knowledge

par Enzo D G M

8 nov. 2020

I learned very much with this specialization, was funny and powerful

par Abishek S

20 juin 2020

Slightly more difficult than the other courses, but very informative

par Nadhifa S

16 juin 2020

GREAT! I learn A LOT from this. Thanks very much laurence & andrew!

par Kota M

11 août 2019

I think there should be graded problem sets for effective learning.

par Darko C

26 janv. 2021

The course should have a mandatory programming assignment as well.

par Karunanidhi M

19 sept. 2019

Helped me solve a real-time Prediction Challenge Excellent Course.

par Aleksandr S

24 janv. 2021

The course was great. I learned a lot for practice in TensortFlow

par Volodymyr S

29 nov. 2021

Освежил и дополнил знания полученный от старых курсов Andrew Ng

par Avinash S

8 mai 2020

I Loved it,

Looking forward to next specialisation tf deployement

par maxime c

7 mars 2020

Great course. A second course with more complex models is needed

par Vidush R

2 déc. 2019

One of the best course in coursera, looking forward more courses

par Fernando W

2 févr. 2021

Great course! I recommend taking it along to Andrew NG's course

par afshin m

18 janv. 2020

This course is much better organized than the NLP (3rd) course.

par Muhammad Y

13 sept. 2022

Best course I have ever learned and instructor was very well.

par priyanshu

24 juin 2022

best course on time series . And for deep learning time series

par Juan C B G

27 nov. 2020

Es un curso muy bien dado, de manera prática y bien explicado.

par han

3 mai 2020

Great course, Looking forward to pro course for tensorflow 2.0

par Francisco R

21 avr. 2020

I would have to do more exercises with multivariate, multistep