Chevron Left
Back to Sequence Models

Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
30,473 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

WK

Mar 13, 2018

I was really happy because I could learn deep learning from Andrew Ng.

The lectures were fantastic and amazing.

I was able to catch really important concepts of sequence models.

Thanks a lot!

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

Filter by:

1451 - 1475 of 3,710 Reviews for Sequence Models

By Jeffrey V V

•

Jan 14, 2019

I learned a lot about how to put together recurrent neural networks.

By sunaram p

•

Feb 7, 2018

A very good intro to NLP/Speech Recognition with Deep Learning (RNN)

By J L

•

Sep 6, 2022

Thanks to Andrew for his heartfelt teaching,I have benefited a lot.

By Shaswata D

•

Jun 1, 2020

Good course for understanding and building rnn for sequential data.

By Nazmus S

•

Aug 15, 2019

iPython Notebook kept crushing which was a disappointing experience

By Mark L H

•

May 10, 2018

Nice mix of simple and complext concept plus good exposure to Keras

By David B

•

Mar 12, 2018

Thanks a lot. That was a very good introduction to sequence models.

By car s

•

Feb 23, 2018

Great lecturer. Best explanations to GRU and LSTM I have even seen.

By Justin H

•

Jun 11, 2023

Insane! Not only has the gradients exploded. my head as well...

By Egor F

•

Jan 18, 2023

Very insightful even if you're already an experienced ML engineer.

By Julio A

•

Apr 17, 2022

A great course and very much what you would expect from Andrew Ng.

By Francesco F

•

Feb 12, 2022

Great Course: Solid Theoretical Approach, Representative Exercises

By Nghĩa P

•

Jan 1, 2022

Hard course but fruitful thanks Coursera for giving me opportunity

By Abdulrezzak Z

•

Jan 20, 2021

One of the most interesting and useful courses I've ever attended.

By Martin E

•

Dec 31, 2020

Aprendí muchas cosas nuevas. Ahora es hora de ponerlo en práctica!

By Barata T O

•

Dec 19, 2020

Easy to understand explanations, interesting programming projects.

By Vishnu N

•

Oct 25, 2020

ThankYou Andrew Ng for this interesting course on Sequence Models.

By Adikwu U S

•

Jun 17, 2020

Great content and delivery that make advance concepts look simple

By LAAVANYA M

•

Jun 14, 2020

Wonderful experience and lots of experiments to enhance our skills

By James G

•

Jun 13, 2020

This course helps me a lot! Thank you all for this amazing course!

By Juan C L

•

May 30, 2020

I learning the mostimportant subjects for may professional profile

By Sujatha r G

•

May 18, 2020

It was very fantastic session, gained much knowledge .Thanks a lot

By Jamal A

•

Apr 3, 2018

Learnt a lot! Great effort by Prof. Andrew NG, highly recommended.

By Tuyên Đ

•

Jun 20, 2020

it is perfect course for who want to learn sequence model and NLP

By Nebojsa D

•

Sep 5, 2019

Good teaching sessions. Problems with automatic grader at the end