Chevron Left
Вернуться к Sequences, Time Series and Prediction

Отзывы учащихся о курсе Sequences, Time Series and Prediction от партнера deeplearning.ai

4.7
звезд
Оценки: 4,248
Рецензии: 680

О курсе

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....

Лучшие рецензии

OR
3 авг. 2019 г.

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.

MI
6 июня 2020 г.

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.

Фильтр по:

551–575 из 680 отзывов о курсе Sequences, Time Series and Prediction

автор: Michalis F

1 окт. 2019 г.

overall good... but was expecting a bit more of it , being the last course in the specialization

автор: Manish G

22 авг. 2019 г.

Good course it gives you quick start on practical aspects of Deep Learning techniques. Nice!

автор: Igor B

18 мар. 2020 г.

Very good course, but for me is much better Andrew NG style, when he writes on "blackboard."

автор: Saeif A

24 авг. 2019 г.

I wish there was graded assignment as the quizzes are shallow and not enough to practice.

автор: Javier A

30 сент. 2020 г.

I would add some code assestments and challenges as requested for the previous courses.

автор: akshay s

25 янв. 2020 г.

This is just univariate time series . You should also teach multivariate time series.

автор: rajesh t

12 янв. 2020 г.

need to be more advanced, with realistic data and problems. Do not use textbook data.

автор: Alice M

8 дек. 2019 г.

expand on why you choose certain code. add more references for learning python better

автор: BOBBY J I

1 сент. 2020 г.

Nice practical course. However, it doesn't cover multivariate time series prediction

автор: Eric J

12 окт. 2021 г.

W​eekly Examens should be harder, but the "learning" content is typically perfect!

автор: MD. N S N

17 сент. 2020 г.

If the sound quality is more loud & clear then this course becomes more fantastic.

автор: Wan N

20 июня 2020 г.

This course is interesting and I have learned a lot of staff. Thank you, Laurence!

автор: Dr. W G v d S

30 апр. 2020 г.

This is a really good introduction into the time series and sequences prediction.

автор: Neel A

31 авг. 2020 г.

The optional exercises should be graded, it was fun there, rather than the quiz!

автор: Md S H C

17 авг. 2020 г.

Overall a good course. Would be a 5-star if there were some graded assignments.

автор: Azazul I

24 авг. 2020 г.

graded programming assignments and variation in examples should be imported.

автор: Abhishek M

19 июля 2020 г.

Great course!! However, there are some question that were left unanswered.

автор: Rob S

4 сент. 2020 г.

Probably the toughest course that could have done with more explanation.

автор: Sai K K K

11 янв. 2020 г.

Concepts and Importance of Fine tuning the parameters well explained!!

автор: Pak S H

30 авг. 2019 г.

It will be better if there is also a multivariate time series example.

автор: Hemali R

23 авг. 2020 г.

Very good! Good if you showed us how to work with our own data set

автор: Mukul A

7 июля 2020 г.

A few bugs present, but overall a good a course and specialization

автор: Gerardo S

2 дек. 2020 г.

I would have liked if they were more explicit about window sizing

автор: Devwrat N

30 сент. 2019 г.

Every step in programming should have been explained in detail

автор: Fülöp C

26 апр. 2021 г.

The quality of the exercises were below my expectations