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Вернуться к Sequences, Time Series and Prediction

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

4.7
звезд
Оценки: 4,195
Рецензии: 675

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

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.

JH
21 мар. 2020 г.

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.

Фильтр по:

651–675 из 675 отзывов о курсе Sequences, Time Series and Prediction

автор: Leonardo

21 дек. 2020 г.

I have done the initial Deep learning courses of Andrew, and they were very thorough and well explained. I was expecting the same quality, however, it was not so. Explanations were generally good, but the examples and the details around the architecture of the models were barely discussed or considered, besides pointing me to the next course (which I have done). I was a bit disappointed TBH, for an "applied" course I do not think this provides enough material to begin applying this knowledge into real life problems.

автор: Joanne R

8 сент. 2019 г.

Really poor quality, sadly. The notebooks are full of errors, the quizzes are mostly coding questions instead of being about deeper understanding of the notions studied, and I don't think the videos are clear enough about what decisions are most important when building this type of model and how to make those decisions. Love the topic, but very disappointed, and don't think this is worth what I'm paying..

автор: Andrei I

13 февр. 2021 г.

The course is merely a walk-through some Jupiter notebooks of Laurence. There are no proper slides with explanation of what's going on. I also don't see much activity from the course creators on the discussion forums. It is incredibly easy to complete the course without forming any deep understanding.

The weekly programming exercises are not even automatically checked for accuracy.

автор: Praful G

22 мая 2021 г.

If you already have good knowledge of Neural Networks like CNN, RNN, LSTM, etc. then only opt for this one. Because they keep referring to previous courses in the specialisation for these. Also, they are only writing the code but never cleared about, what they are writing and why.

автор: Ebdulmomen A

26 сент. 2020 г.

quiz's are pathetic! throughout the whole course the instructor talks about the advantages of RNN and LSTM and CNNs for time series prediction while not being able to prove this not even for one in the entire course, what a disappointment !

автор: Kaushal T

5 авг. 2019 г.

The course was not as detailed or in a flow like I expected from a deeplearning.ai course and the editing was also very bad, one thing was shown and something else was spoken.

автор: Victor H

11 сент. 2019 г.

A bit too high-level with lacking explanation on intuition. E.g. Conv1D was added to LSTM layers which helped reduce loss value, but did not go into the explanation of why.

автор: Tomek D

29 февр. 2020 г.

Course is very quick and does not cover the topics in sufficient depth - explanations and discussion are all very brief.

автор: Akiva K S

7 сент. 2021 г.

Junk course. Andrew Ng is a great specialist but I'll never try courses from deeplearning.ai.

автор: Yevhen D

13 февр. 2021 г.

This course will be good only for very beginners. It's not deep and challenging enough.

автор: Sergey K

22 окт. 2020 г.

To make it better you have to develop more challenging and GRADED! exercises

автор: Sujin S

5 окт. 2019 г.

Poor audio quality.. Cant even hear in full volume

автор: Gabor S

25 июня 2020 г.

Very bad quizzes, no challenge whatsoever.

автор: Bojiang J

12 мар. 2020 г.

Too much repetition in the content.

автор: Ankit G

21 мая 2020 г.

Could have been better

автор: Magdalena S

30 мар. 2020 г.

Too easy.

автор: Xiaotian Z

25 нояб. 2020 г.

I do hope that the deeplearning.ai team could spend more time polishing the materials instead of just throwing the Tensorflow docs/sample codes and going through them superficially. Please also change the instructor as I really doubt his professionalism/experiences in ML practices despite his titles. Please, please don't ruin your brand, deeplearning.ai. I wish to see more in-depth courses like the ones taught by Andrew.

автор: Robert

2 апр. 2021 г.

Maybe I had wrong expectations from this course. But to me it felt like the material in this course was extremely superficial. I was hoping to learn something, but it turned out to be a very basic overview of the material. Everything boiled down to "compile + fit" without the explanation of nuances associated with time-series settings.

автор: Brad N

21 сент. 2020 г.

The last two parts of this 'specialization' were pretty much useless. Here's some code, let's look at the code three times, let's take a kindergarten quiz, let's look at the same code again, here's the answer you can copy if you bother doing the exercise.

автор: Yanghao W

17 февр. 2021 г.

This is a quick introduction of using TensorFlow for prediction without any explanation for helping students understand the codes, the rationale, and the technical details we need to know for doing practice in daily work.

автор: sukanya n

23 сент. 2020 г.

Gives a very shallow understanding. You can easily pass the quizzes without even needing to go through the colab code notebooks. This is unfortunately quite a good example of 'money can buy you a certificate'.

автор: Sidharth N

4 авг. 2020 г.

Extremely shallow ML course, with certain videos showing nothing more than running a few code snippets. More depth and explanation could go very far in improving the overall experiece

автор: Arun A

6 авг. 2020 г.

Really disappointment. Wonder what is purpose. After few videos it seemed like synthetic data is created just to create course. Lost interest very quickly

автор: Maged A

18 нояб. 2020 г.

Extremely shallow. It's just to have an initial idea but not in depth.

автор: Mehmet O

4 апр. 2021 г.

To be honest course content was realy week.