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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
29,838 ratings

About the Course

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career....

Top reviews

MK

Mar 13, 2024

Cant express how thankful I am to Andrew Ng, literally thought me from start to finish when my school didnt touch about it, learn a lot and decided to use my knowledge and apply to real world projects

JY

Oct 29, 2018

The lectures covers lots of SOTA deep learning algorithms and the lectures are well-designed and easy to understand. The programming assignment is really good to enhance the understanding of lectures.

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2851 - 2875 of 3,620 Reviews for Sequence Models

By Artem M

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May 29, 2018

This is a very interesting course with good explanations, which give a brief but sufficient introduction to sequential models like GRU and LSTM. One star is dropped because the CNN course (#4) is still better than this one in terms of explanations, while course #2 is better in terms of relevant material and pace (to me).

By Pascal P Z Z

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Jan 19, 2020

Although I really really really love this series and although I always gave 5 stars, I think the quality of this last module is a lot less better than the previous ones. I think convolution was way more difficult but the explanation was awesome. Unfortunately, i think explanations in this module are a little sloppy.

By Peter S

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Jun 7, 2019

As usual, Andrew Ng's stellar talent as an educator shines through. Unfortunately, some of the video editing is a little scrappy, and the assignments could use some more polish. Especially in areas where they catch quirks in the grader. Luckily the forum support is excellent. This course is definitely worth doing.

By vishnu v

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Feb 15, 2018

Overall nice course, learned a lot about NLP and Speech to text. Course is more oriented towards NLP applications, I was also hoping to learn more about time series analysis. Feel like the course could have been longer 4-5 weeks since RNN, LSTM and GRU is pretty long topic and 3 weeks seems to be too short for it.

By Dunitt M

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Apr 26, 2020

Recomiendo ampliamente este curso, te proporciona un claro entendimiento de los modelos secuenciales y recurrentes. Es excelente, aunque a diferencia de otros cursos de esta especialización no explicaron en detalle algunos aspectos de las RNN, me hubiese gustado que profundizaran un poco más en backpropagation.

By chandrashekar r

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Feb 6, 2019

The RNN, LSTM< and GRU were very good. But the Week 3seemed a bit abstract. More could have been covered in Audio, Attention.

ALso the Jupyter Notebooks was frequently crashing, and it took lot of attempts to re-open the existing one. Lot of time wasted. Also it took long time to to submit and run the program

By Eysteinn F

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May 27, 2018

This course provided a nice high level overview of RNN models and associated Keras implementations. The tricks and tips given were a useful addition to my ML arsenal. The only thing that I feel discredits this course is that the programming assignments are easy to gloss over and pass without much engagement.

By Bill T

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Mar 19, 2018

Great introduction to RNNs and how to implement them in keras. I suspect it is a relatively new course as there are still typos and a few errors in the assignments (otherwise I would have given 5 stars) but the forums help you to find your way around them and hopefully in future versions they will be fixed.

By Amir T K

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Dec 5, 2019

Excellent lectures, some part was difficult and it took time for me to imagine the content of each parameter (e.g. when we talk about X, or a, or Waa what is the size of them and what do they represent). But in the exercises, it became more understandable. Exercises need previous knowledge of Keras and OOP.

By Shuxiao C

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Feb 5, 2018

It is a fabulous course content-wise. However, I personally find the programming exercises overly easy (the instructors already build the framework for you and the only thing you need to do is to fill in the blanks), s.t. I'm still not able to build an RNN from scratch after completing all those exercises.

By Tien H D

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Jul 10, 2018

This course is good. It introduces the concepts regarding recurrent models. I specially like the attention model videos. In general, the exercises are well written. However, I'm not very familiar with Keras and working on the Keras code really takes my time even I'm quite experienced with Tensorflow.

By Ting C

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Jul 20, 2018

Professor Ng did a good job explaining sequence model and I finally understand the basic theories. However, there is room to improve especially on the Keras library part. I hope you can add some simple tutorial for that. Also, I still don't understand how to translate the architecture to Keras code.

By Vijeta D

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May 4, 2020

This is a very well structured course. I initially started this course almost 10 months ago but got distracted and started to learn sequence models on my own. But, at the end end I resorted to this course again and got my basics cleared out. Thanks to deeplearning.ai team for designing this course!

By Alberto H

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Feb 23, 2018

Great explanations on the videos, and well designed programming exercises. However, the complexity of the programming tasks is not well dimensioned (1h - 1:30 h may be too little). Worse, some of the exercises are not well explained, with misleading information (e.g. about model tensor dimensions).

By seshouan

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Dec 13, 2023

While Andrew Ng's lectures are great and engaging, the weekly lab assignment prompts leave a lot to be desired, as the explanations are often confusing, misleading, not straight forward, and out of order. These labs should be overhauled for greater clarity and ease of completion and understanding!

By K173664 S K

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Nov 4, 2020

this is a well structured course, but it is not for beginners at all, andrew ng had put alot of his efforts in this. As a computer science major, I was able to grasp the maths concepts but for anyone comming from diffrent background its far from possible to understand all the theoratical concepts.

By Pedro H B D

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Aug 30, 2019

There was not enough theory as the first three courses. Some explanations were superficial and difficult to understand. Maybe drawing the shape of the inputs, outputs, and other matrices in lectures would help to better visualize what's going on inside the networks. Overall, it was a great course.

By Miguel S

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Nov 27, 2019

It's a great course. The information and knowledge that you get about Sequence Models is fantastic as a primer. Andrew is an amazing teacher throughout the entire specialization altough I found the content of the videos in the Sequence Models slightly more rushed than the previous 4 courses...

By Daan v d M

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Nov 16, 2020

The theory was absolutely interesting and an eye-opener. The programming exercises were hard to make because of the keras/tensorflow knowledge and I actually ended up just fill-in in things, as were given in the examples, without really knowing what I was doing. Time for a Tensorflow course.

By Thiago H M

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Apr 18, 2019

Poderia dar um pouco mais de instruções na hora de usar as funções do Keras. Ficou um pouco confuso.

No assignment da semana 3 (Machine translation). Tem um output que não precisa estar exatamente igual mas o curso não fala isso e acabei gastando bastante tempo nisso, só vi depois no fórum.

By Sujay B

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Apr 9, 2018

Though the lessons are interesting and mathematically demanding, I felt that it was a good time spent learning these concepts. Overall I feel that the 3 weeks could be split into 4 weeks and learning could have been much smoother by adding some more lessons to address the contents of Week 2.

By Juan S C

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May 9, 2022

I Love it! every single part of the course!

The reason I give it 4 stars is to get the attention of the developers and lecturers of the course.

Please, please, please improve the customer service of coursera. Please give the site deeplearning.ai more support from lecturers and people experts.

By Anna C

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Jun 23, 2019

Nice content, but the assignments are too easy and only demonstrate the pipeline instead of providing hand-on experience in picking the network and training with GPU. Also, there are some grader problems which has wasted my time to make my code pass the grader even if the answer is correct.

By Jingbo L

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Mar 16, 2018

The homework grading methods need improvement. I got the right model and get the right results, but still have to spend tons of time to make the submission pass the grading system. It is a waste of time for future learning. You may want to train a DL model to solve this grading problem :).

By Richard M

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Oct 25, 2020

Great explanation of theory (RNNs etc.) and easy to follow course structure. The programming exercises are disappointing though: They mostly consist of mindlessly copying Keras functions without an understandable (!) explanation. Many provided links to the Keras documentation are outdated.