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

Оценки: 4,300
Рецензии: 686

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 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

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.

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 686 отзывов о курсе Sequences, Time Series and Prediction

автор: Gerardo S

1 окт. 2019 г.

a little bit to light

автор: Artem K

17 сент. 2020 г.

Plz more practice :)

автор: Kai J J

22 авг. 2020 г.

A little to easy.

автор: Neshy

6 февр. 2021 г.

too easy

автор: Masoud V

23 авг. 2019 г.


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: Amairani Y V C

21 дек. 2021 г.

Me parece que no dan un buen enfoque a muchos puntos, los códigos no se explican bien, y abordan temas que son densos en minutos lo cual hace que quedes sin mucha información. No me parece que sea un buen curso por eso.

автор: Kaushal T

5 авг. 2019 г.

The course was not as detailed or in a flow like I expected from a 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

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: Anant G

28 нояб. 2021 г.

It is a surface-level introduction

автор: Ankit G

21 мая 2020 г.

Could have been better

автор: Magdalena S

30 мар. 2020 г.

Too easy.

автор: Adam F

1 нояб. 2021 г.

This specialization is false advertising. It does NOT prepare you for the Tensorflow certification exam. It’s especially disappointing after taking the fantastic specialization by Andrew Ng, and makes this specialization feel like a cheap cash grab by Coursera and This series of courses fails to prepare you for three reasons:

1 – The certification exam is done on whatever is the current version of Tensorflow (v2.6 as of writing). You can’t expect a specialization like this to update every minor release, but much of the coding is still on the v1.X version!

2 – The certification exam requires you to work in the PyCharm IDE. The IDE doesn’t even get a mention in this specialization and it is all done through Google Colab.

3 – The material is covered at a very superficial level. I was hoping to walk out of it feeling confident in using Tensorflow on novel problems, but I’ve barely learned anything about Tensorflow that I didn’t already get from Andrew Ng’s specialization. There’re a few minutes of lectures (some weeks less than 10 minutes). The programming assignments are either pathetically easy, or lack any guidance on what to do (seriously sometimes there’s no instructions at all, you have to guess what to do by the variable names), or both.

Save your time and money and go elsewhere to learn Tensorflow.

автор: Albert Z

12 дек. 2021 г.

Even worse than the NLP course. Week 1~3 contains nearly no new material for tensorflow. It's just some replicated knowledge from previous courses. Studying synthetic data is good, but is off-topic for a tensorflow course. The course should focus on models and model structures for different types of time series data. My biggest complaint is that this course does not cover even the basic knowledge required by the tensorflow certificate exam (as advertised). Where is the multivariate time series forecasting? This is the most important part of the exam but the course totally neglects that.