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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
30,390 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

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.

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

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3101 - 3125 of 3,693 Reviews for Sequence Models

By Tiago C G M

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Mar 3, 2019

The course is really good, I would recommend it to anyone who wants to learn the subject, but it lacks support from the staff in the discussion forums.

By Tomasz D

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Oct 3, 2020

Very good course. Some editing issues in the lectures and small issues with the programming exercises (outdated Keras instructions and documentation).

By Nicola P

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Feb 14, 2018

The lectures are excellent. The assignments are an extremely valid trace of significant deep learning application, while they lack a bit of challenge.

By Inna U P

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May 22, 2024

Gennerally structured well. The explanation about the position encoder weren't very clear for me so I found other videos on youtube that explain it.

By Alon M

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Oct 13, 2018

As always, this course is great. however, for some reason this course is much more difficult then the others, and i feel as if it is packed too much.

By Michael S

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Jul 12, 2018

Really good course, like the others. A bit too black box in some of the programming exercises, so I expect to struggle when developing my own models.

By Ethan X

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Apr 10, 2018

The videos are really informative and well structured. However, the exams felt like Keras tests. A detailed Keras tutorial would have been helpful.

By Takeo S

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Mar 28, 2019

It was great course,

I wish we have more speech recognition contents

Hope, you add new course a bit focus on audio/speech recognition etc

Thank you!

By Alex E

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Jan 3, 2023

The only reason I'm not giving it a 5 is the course 5 week 4 coding assignment. See my comments in response to post by @marcus-waldman for detail

By Ara B

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Dec 31, 2019

too much content and not much chance to exercise. I will suggest for more frequently and smaller programming assignments through out the course!

By Sohel A

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May 31, 2023

Awesome course. I got to learn about Sequence models(GRUs, RNNs, LSTM, Transformers...) and how they are used in today's exciting applications.

By Rodrigo N S

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Feb 17, 2021

Outstanding course, but the end of it uses many architectures not fully explained (GRU and such). Incredible course and specialization, though!

By Reda M

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Oct 19, 2020

Excellent course, but I would have liked to work on predictive maintenance examples leveraging RNN and LSTM networks. Big thanks to whole team.

By Nishant B

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Aug 11, 2019

The course is nicely designed and every topic is explained in a very lucid manner by Andrew Ng. Must be done as a beginner in sequence models.

By Suraj S J

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May 20, 2019

Simplified content delivered in just the right way to give a perfect intuition of the complex concepts. Really enjoyed doing the whole course.

By Harry T

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Jan 17, 2019

Great content, but Andrew often starts his phrases then restarts saying them. Audio could use some cleanup, then this course would be perfect!

By Yunhua J

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Jun 11, 2018

Most optional assignments contain bugs/errors. Other than that, this is a great course, just as the 4 other courses in this specialist series.

By 王煦中

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Feb 3, 2018

I give 4 star because some fomulas are not correct! Though this course is really great. I can not understand why you made mistakes on fomulas.

By Makito K

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May 25, 2021

Great materials and programming exercises. The programing exercise in week 4 could be improved for the more beginner-friendly style probably.

By Rohit T

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Nov 22, 2018

This one seemed to go through to quickly over the details especially with the word vectors and the LSTM, would have appreciated more examples

By Joris D

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Feb 16, 2018

Very good course, though the assignments towards the end were a little too centered around Keras, which I personally don't care for very much

By Pui L L

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Feb 21, 2018

The instruction of using Keras in the programming assignment is unclear. There are many bugs as well, hence we have versions 1, 2 and 3 etc.

By Ruben Y Q

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Apr 27, 2020

No time series analysis, and some problems in the guidance of some programming tasks. Mainly de first week, the rest of it was pretty good.

By Jean-Michel C

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Jan 12, 2019

Good course. I would suggest to split the first week into 2 weeks, which makes easier to grasp all the concept with a deeper understanding.

By Yizhe

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Jun 24, 2021

Some assignments don't have enough descriptions to help me deeply understand the core concept of the algorithms. Hope it can be improved.