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学生对 deeplearning.ai 提供的 序列模型 的评价和反馈

4.8
27,670 个评分
3,305 条评论

课程概述

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....

热门审阅

AM

Jun 30, 2019

The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.

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!

筛选依据:

251 - 序列模型 的 275 个评论(共 3,306 个)

创建者 Zhiming C

Jun 14, 2020

This course introduces the basic idea of RNN, GRU and LSTM models. They are obviously harder than the CNN models and the concepts are not so easy to understand. Thanks to the systematic introduction! Together wit the excises I can understand better the theory from the applications. It's great!

创建者 Andrei N

Sep 21, 2019

The content, examples, assignments, and quizzes are thoroughly developed. All the courses of the specialization share the same notation and lead a student from basic concepts to complex ones helping to develop an intuition on each step. The best course on topic of Deep Learning one could find.

创建者 Nilesh K S

Dec 5, 2018

It was a great experience to learn from Andrew NG and it helped a lot to me personally and professionally. I have gained so much confidence after completing these set of 5 courses and looking forward to build some cool projects on my own using the concepts that i have learned in past 5 months.

创建者 Mihir T

Sep 23, 2018

A great course on latest technology used in NLP. The course is well structured and provides an in-depth knowledge on sequence models. This course is a all-in-one package for starting your career in NLP. Mr. Andrew is a great teacher, and explains everything in a very simple yet effective way.

创建者 Wesley H

Aug 8, 2019

Great finish to the specialisation. I have learned a lot of the core details of how to proceed with my own Deep Learning projects. My one piece of feedback would be for an intermediary step, that requires more of the programming myself, as a lot of the intricate coding has already been done.

创建者 Challa S

May 7, 2020

The course content is very good but the mistakes in the videos are being mentioned after the video. This is making us get confused a bit. It would be good if those errors are mentioned before the video itself so that we can look into that before watching the video and get prepared for that.

创建者 Wingyan C

Mar 1, 2022

Excellent teaching, materials, and organization! It's great to include state-of-the-art technologies like Transformer and LSTM. I would recommend also teaching some practical skills (like TensorFlow) that students can apply directly in practical programming (beyond the course assignments).

创建者 Isaac S J C

Nov 5, 2018

Great appreciation to Dr. Andrew Ng. The course has been incredibly well taught. Thank you so much for your enlightening lectures. I very much enjoyed the course, and I think it is very well structured and organized. The forum was very helpful when I got stuck in the programming exercises.

创建者 Anujay S

Sep 30, 2019

I am amazed with the learning experience of Seq2Seq Modules created by deeplearning.ai team! Loved the way it's taught by Andrew Ng and the hands on experience helped the mentee very well. Keep building such courses, would like to contribute more in this space as in research or products.

创建者 Kyle L

Feb 15, 2018

Insightful detail on model architectures and how they influence (and are influenced by) data generation for sequence-based applications. For those that have grasped the theory behind DNNs and are interested in applying ML to language and text, I highly recommend checking out this course!

创建者 Almadani

Apr 7, 2021

I like the course. It's beneficial and clear. Also, the concept is clear.

for more improvement

I would suggest that for jupyter implementation :

I hope you put 2 versions of the code

thus, the student can have a choice to work on a famous frame

1- using Tensorflow (TF)

2- using PyTorch

创建者 Kumar S

Aug 30, 2019

This course was really awsome,learning has been fun in all the 4 courses, the number of new things learnt in this course was remarkable.Even the mot complicated things were taught in such a way that it never seemed tough.Doing assignments really helped to make concepts even more clear.

创建者 Lee F

Feb 17, 2018

Fantastic course! Presents both the theory and practical uses in a straightforward manner that is easy to grasp. Programming assignments are a mix of NumPy and Keras API, with the former being more illustrative of the inner workings of RNNs and the latter being more practically useful.

创建者 Nicolas C

Feb 17, 2018

Excellent! Amazing! Such good quality of lecture and assignments. Thank you Andrew and team for giving me such a good overview of what i can use this for. I feel as though this series dramatically lowered the barriers to entry for me to get started on any ML project i decide to. Thanks

创建者 Manmohan K

Jul 2, 2020

No better introductory material. I suggest doing NLP specialization by deeplearning.ai after this though I have still not tried it out myself yet but hoping to do it some time. Thank you Andrew! I got emotional in your last video of the course. You are such an example for educators <3

创建者 Aman K

Feb 13, 2018

This was by far the Best Course and Specialization that I have done. Thank You Coursera and Thank You Sir Andrew NG . You have made me confident and able in the Field of Deep Learning. I am grateful to you Sir. I will try my best to use this knowledge as a superpower in the right way.

创建者 Laks P

Apr 30, 2022

1) Course over all is good.

2) I had a slight difficulty understanding the WW4 section, Transformer concept "guts" even though I happed to score 100 on the course. Possibly with some more practice, I should be able to understnd Transformer, multi-head attention model concepts better.

创建者 Leonardo E T C

Mar 29, 2021

In my opinion, this module was a little more complex than the previous ones, however, it has been an excellent course to deepen my knowledge in recurrent neural networks and close this specialization program in deep learning. Thank you very much, Dr. Andrew Ng and deeplearningai!!!!

创建者 Liyan X

Jun 3, 2018

Great course with interesting exercises. One can really see the amount of effort being put into creating the assignment material, so they are at a suitable level and with a lot to take away, and the students have a good understanding of details through practice. Really appreciated.

创建者 Yirong Z

Jan 7, 2022

I don't know how to express my feeling of gratitude. The DeepLearning Specialisation to some degreee, changes my life, including career and reserach. I will definitely make fully use of this superpower to improve humanity and the whole community! Thank you again to deeplearning.ai!

创建者 anand k

Apr 2, 2020

the programing assignment ins WEEK 1 was a bit ambiguous in nature. helped me improve my debugging skills.

Also a huge thank you to MENTOR Mr. GEOFF for the instant support to all my queries. His way of providing HINTS lead me to finally complete the course. a BIG thank you to him.

创建者 Manhal R

Jun 21, 2020

More easier to understand than the ConvNets course!

Week 1 and 2 took me a little time to get through. Week 3 is easy.

For better understanding, don't forget to download the notebooks and practice on your own local Jupyter notebook while using the assignment notebook as a reference.

创建者 Jayash K

Jul 6, 2018

This is a great course. It provides a good introduction to RNNs and how they are used in sequence modeling. Introduction to GRU, LSTMs, BiRNNs, attention model is great way to learn these in depth. The exercises are designed to make you familiar with the internals of these layers.

创建者 Dong Z

Aug 18, 2020

At the beginning this is very counter-intuitive. But later on when I am on the final assignment, I finally realized that we are not focusing on gradient descent, but architecture building and training set assembling! When everything start to make sense, it is really intriguing.

创建者 Kyung-Hoon K

Apr 29, 2020

This course made me have great understanding around the Sequence Models such as GRU, LSTM, Attention, etc. I had a lot of fun while completing programming exercises such as Trigger word detection. As always, it was one of the best class ever. Thanks Professor Andrew Ng and all-!