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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
26,488 ratings
3,125 reviews

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.

WK
Mar 13, 2018

I was really happy because I could learn deep learning from Andrew Ng.\n\nThe lectures were fantastic and amazing.\n\nI was able to catch really important concepts of sequence models.\n\nThanks a lot!

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2701 - 2725 of 3,095 Reviews for Sequence Models

By Javier L P

Apr 17, 2020

Missing the notes in between the videos like in the Intro to Machine Learning course

By Keith l

Sep 12, 2018

some of the auto graders were a bit buggy, but overall loved the course and material

By bangdasun

Feb 19, 2018

Nice content. Spend some time on homework since I'm not very familiar with keras.

By Yu L

May 21, 2020

coding style is out-of-date. Could the TA update the coding homework regularly?

By Boyu L

Mar 15, 2018

I wish there was a more thorough tutorial on the Keras programming environment.

By Saurabh

Feb 11, 2018

Another awesome course. But I feel Word Embeddings part could have been better.

By Moustapha M A

Mar 14, 2018

A very good course in terms of application , again Dr. Ng did an excellent job

By Umair

Nov 27, 2020

This is amazing course with much more interesting labs and practical examples

By Kevin H

Mar 8, 2019

The course is great but I was hoping to have a part about time series inside.

By 林昌璟

Dec 27, 2020

It's pretty difficult for me, but I learn a lot of knowledge in this course.

By Shengwei W

Jul 27, 2020

Great Course on giving an Introduction to RNN and basic NLP architectures !!

By Yogesh J

May 26, 2020

Please allow students to complete assignment from scratch. Without any help.

By Philippe T

Oct 29, 2018

More exemple than Only NLP would have been nice ! But overall a great course

By Emanuel V

Apr 2, 2018

This is a good course. However, this topic deserves much more detailed work.

By J V

Apr 24, 2020

Great Content with real-time example looking forward to doing more courses

By Andrius T

Nov 2, 2019

Please remove repetitions from videos, really annoying thing. Great job :)

By Luca C

Oct 13, 2019

Awesome notebooks to gain practical experience with deep learning systems.

By Philippe A

Oct 21, 2018

This course is very interesting! Again! It requires basic Keras knowlegde.

By EZ

Feb 18, 2018

Course is excellent. Assignment, however, could use some more refinement.

By Attili S

Aug 12, 2020

It would be good to extend some more detailed explanation in this course

By Sebastian M

Apr 7, 2019

need some reviewing in the optional parts of the programming assignments

By Guan W

Mar 10, 2018

Excellent course content, but poor maintenance of programming assignment

By Filip V

Feb 25, 2018

Provides good exposure to sequence models for NLP and speech processing.

By Xirui Z

Apr 7, 2021

Instructions for labs are not clear enough, especially the layers part.