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

4.7
étoiles
4,453 évaluations
704 avis

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 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....

Meilleurs avis

JH

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.

OR

3 août 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.

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676 - 700 sur 704 Avis pour Sequences, Time Series and Prediction

par Ebdulmomen A

26 sept. 2020

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 !

par Amairani Y V C

21 déc. 2021

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.

par Kaushal T

5 août 2019

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.

par Victor H

11 sept. 2019

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.

par Tomek D

29 févr. 2020

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

par Akiva K S

7 sept. 2021

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

par Yevhen D

13 févr. 2021

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

par Sergey K

22 oct. 2020

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

par Sujin S

5 oct. 2019

Poor audio quality.. Cant even hear in full volume

par Gabor S

25 juin 2020

Very bad quizzes, no challenge whatsoever.

par Bojiang J

12 mars 2020

Too much repetition in the content.

par Anant G

28 nov. 2021

It is a surface-level introduction

par Ankit G

21 mai 2020

Could have been better

par Magdalena S

30 mars 2020

Too easy.

par Adam F

1 nov. 2021

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 DeepLearning.ai. 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.

par Albert Z

12 déc. 2021

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.

par Oliverio J S J

21 oct. 2021

Like the previous course, this is not a four-week course but a collection of short videos that can be watched in one morning. The first week (actually the first hour) provides interesting insights about time series but the rest of the weeks (hours) are a quick review of code snippets. The pace set by a sequence of one-minute videos is excruciating and makes it difficult to follow the lectures. In addition, there are no practical assignments, just some trivial quizzes.

par Xiaotian Z

25 nov. 2020

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.

par Savvas R

8 janv. 2022

Extremely shallow and sloppy made course. It is sad to see that the optimization done in the neural network is at the very least non-robust (if not totally random). The techniques used are simple illustrations that one can find better in youtube videos for free. The fact that people have to pay for this course is basically a scam, you should be ashamed of yourselves.

par Robert

2 avr. 2021

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.

par m b

16 mai 2022

The module on time series did not help at all in the certification exam. It's full of simplistic examples and broken links and optional assignments. All the while, the new iteration of the exam is more complicated and touches on topics not covered in this workshop on time series. Very disappointing.

par Brad N

21 sept. 2020

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.

par Yanghao W

17 févr. 2021

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.

par sukanya n

23 sept. 2020

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'.

par Sidharth N

4 août 2020

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