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Bewertung und Feedback des Lernenden für Sequenzmodelle von deeplearning.ai

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29,056 Bewertungen

Über den Kurs

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-Bewertungen

AM

30. Juni 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

13. März 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!

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676 - 700 von 3,484 Bewertungen für Sequenzmodelle

von Arnav C

14. Mai 2019

Loved this course. It was everything I expected and more. Always had a hard time understanding attention mechanism and Dr Andrew Ng explained it very well.

von Emilian A

16. Apr. 2018

I find CNN/RNN courses very helpful, but I would highly recommend to improve the exercises. Some typo mistakes can result in hours wondering what is wrong.

von Harshal R P

1. Juli 2020

Excellent content and hands on assignments provides the best ever learning experience ever. I would like to thank all the content creators of this course.

von Prashant J

11. Apr. 2020

Its been great journey to complete this course and so many things I learned which will be helpful in many deep learning and machine learning applications.

von Somashekhar H

15. Okt. 2019

As usual Mr.Andrew NG is great in explaining the concepts.I hope to make use of the skills learnt through this course and this one is coming in great way.

von mouette g

11. Aug. 2019

Very interesting course! It has taught me a lot. Special thanks to the Mentors and the Students who gave hints and explanations in the discussion forums.

von Daniel M M

10. Jan. 2019

Extremely clear and useful. Natural Language Processing, Speech Recognition and Automatic Translation are now concepts much more clearer and close for me.

von Laurent J

24. Feb. 2018

Slightly more difficult than the previous course but a fascinating course. Programming assignments require more thoughts but they are real world use cases

von Agustin N

2. Nov. 2020

Great course about sequence models. I think that this is the most hard of the five courses, but at the end you get all about the architecture of the RNN.

von Aswath S

2. Mai 2020

I was highly confused about sequence models before this course. This course is highly recommended. Thanks to the total deeplearning.ai and Coursera team.

von Rajat M

20. Okt. 2019

Amazing Content !

Grateful to Andrew Ng and his Deeplearning.AI team for spending great amount of time and effort to come up with such a quality content !

von Mike O

29. Apr. 2019

Course content and lectures are excellent. Programming assignments have some minor glitches which should be addressed for a course that requires tuition.

von John E S

24. Dez. 2018

Great lectures. Well thought out quizzes and exercises. The only negative point is that the exercises are too easy, they spoon feed too much of the code.

von Janzaib M

24. Mai 2018

Perfect Start for Understanding RNNs, LSTMs, BRNN, Attention and Basic NLP. It gets you up and running with very easy KERAS implementation of the things.

von Andrew S

14. Feb. 2018

The lectures are amazing. The assignments were difficult for me, but forced me to understand the concepts better. Really glad to have taken the course.

von Peter D

11. Feb. 2018

Excellent course that not only provides a good foundation for deep learning in general, but also gives some insights into more recent developments in AI.

von Leonardo P

20. März 2021

That was a really cool course! Specially the last week, where we've implemented many ideas that I knew were possible but had no clue how to! Very nice!!

von Pat S

10. Jan. 2021

This course gives a great foundation to understand sequence models. Assignments help lay out how sequence models work and also interesting applications.

von Subrata S

17. Aug. 2019

Very much satisfied, to its content. Learnt a lot, thanks a ton to Prof. Andrew Ng for your hard work on its topics & how making learning easy.

😁️☺️👍️

von Marcus B

28. Juni 2019

Very effective at improving my understanding of RNNs (and its variants), Natural Language Processing, and some basics regarding working with audio data.

von Vaibhav K

1. Dez. 2022

This is an awesome course I recommend who really want to learn deep learning step by step. It was really comprehensive theoretical and practical guide.

von AasimBaig M

2. Aug. 2020

This has been an excellent journey and I personally learned a lot from this courses. I want to thank AndrewNg for being the best teacher I ever had. <3

von V V

14. Juni 2020

This specialization really helped me understand DL thoroughly. I really thank Coursera and Andrew's team at Deeplearning.ai for this wonderful content!

von Srividhya S

1. Mai 2020

Awesome assignments. This course was a little difficult to understand but the assignments helped in understanding some of the complex topics discussed.

von Benjamin S S

15. Aug. 2018

Great course, but needs more checks for understanding during the lecture. Course would also benefit with a dedicated module on TensorFlow and/or Keras.