Chevron Left
Zurück zu Natural Language Processing with Probabilistic Models

Bewertung und Feedback des Lernenden für Natural Language Processing with Probabilistic Models von deeplearning.ai

4.7
Sterne
1,286 Bewertungen
230 Bewertungen

Über den Kurs

In Course 2 of the Natural Language Processing Specialization, you will: a) Create a simple auto-correct algorithm using minimum edit distance and dynamic programming, b) Apply the Viterbi Algorithm for part-of-speech (POS) tagging, which is vital for computational linguistics, c) Write a better auto-complete algorithm using an N-gram language model, and d) Write your own Word2Vec model that uses a neural network to compute word embeddings using a continuous bag-of-words model. By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text, and even built a chatbot! This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper....

Top-Bewertungen

NM
12. Dez. 2020

A truly great course, focuses on the details you need, at a good pace, building up the foundations needed before relying more heavily on libraries an abstractions (which I assume will follow).

HS
2. Dez. 2020

A neatly organized course introducing the students to basics of Processing text data, learning word embedding and most importantly on how to interpret the word embedding. Great Job!!

Filtern nach:

201 - 225 von 229 Bewertungen für Natural Language Processing with Probabilistic Models

von Aung Z P

14. Juli 2020

I love the way the instructor teach and the course design which is made to be simple but effective

von Mounir H

1. Dez. 2020

I didn't like weeks 1 and 2 too much but I liked week 3 and I really liked week 4.

von bdug

5. Apr. 2021

I liked the lecture, very well prepared. Only the part on metrics was a bit short

von Vladimir V

20. Juli 2020

This is a good course but I would like to see more emphasis on the mathematics.

von Manuel V B

11. Apr. 2021

Great course, but the last week felt a bit messy with submission evaluation.

von Sophie Z

3. Jan. 2021

Not sure if it is on purpose, but W4 labs have repeating content.

von Trần T V

4. Dez. 2021

wonderful course, I learned the fundamental of NLP. Many thanks

von Jinsong T

8. Juni 2021

T​oo basic and going at too slow a pace

von Esakki p E m

11. Apr. 2021

excellent Material & teaching

von AVIJIT J

16. Aug. 2021

G​ood, very good.

von Randall K

14. Apr. 2021

great course

von ugur b

2. Jan. 2022

Veri good

von MoChuxian

31. Okt. 2020

great

von Teresa M B

5. Sep. 2021

good:

* some of the content is well-explained

* provides good solid knowledge about the background and implementation of common NLP tasks

less good:

* notebooks (and content generally) are unevenly distributed

* significantly stronger focus on ML, rather than on the NL side (this is consistent throughout the specialization)

* some of the explanations (e.g. in week 2) aren't clear

* specialization could be structured better -- word embeddings are introduced in course 1, but the in-depth discussion is here in week 4; would perhaps have made more sense to have that content build on itself

von J N B P

5. März 2021

In this course, you will learn to build an autocorrect model and different methods of building this model. The course felt a bit rushed with a lack of detailed explanation, students who are familiar with the concepts of NLP from before starting this specialization won't face any problem, but students who had just begun learning NLP through this specialization might feel a little difficult.

von Amlan C

17. Sep. 2020

Too many gaps in the course. Many concepts not covered in the mathematical sense basic Grad. Desc. math would have been helpful. Also if you want to omit it totally you should have atleast one lab on how one would do it in real life using which library? Pytorch? Keras? What? Rest of the course is okay. Younous is great in explanation.

von Gent S

8. Apr. 2021

The course material is good and you can learn new things, you can exercise python skills a lot as the assignments are quite long. However, the tutors are not the best in explaining the material as well as the videos are a bit vague. It would have helped if the tutors were a bit more experienced in teaching, but still overall good!

von Aditya J

14. Aug. 2020

well I did deep learning specialization earlier things are mathematical, but here they don't go much into maths, and please make some concept chart, to link different algorithms.

von Chi Z

5. Jan. 2021

BIg bug in week4's assignment! I don't know why not fix it. It turns out that I just train a dummy network

von Tanli H

21. Dez. 2020

The instructors look like reading scripts and indeed a bit awkward.

von DHRUV M

6. Juni 2021

Topics were not clearly taught by instructure

von Nemish K

17. Sep. 2020

This was an okay okay course

von Apoorv G

1. Aug. 2020

Not much useful

von Darren

21. Jan. 2022

Generally good content, but there are several issues. The quizzes for each unit do not always reflect the material for the unit; they are obviously from other units within the course. Many of us have pointed this out on the course forums and reported the incorrect content, but it remains. There are also *lots* of typos and incorrect comments/text/captions in the videos. Some of them have pop-ups that point out the incorrect info, but many do not. The notation is inconsistent between slides in the course and differs even more between the slides and the assignments. It feels very sloppy. I have reported several of these, but no action has been taken. The creators seem to have created the course and walked away leaving a ton of errors and inconsistencies. There does not seem to be ongoing support for the course, even when there are clear, egregious errors.

von Vyacheslav S

11. Jan. 2022

I actually unpleasantly surprised by this course. Completing the whole DL specialization, I used to certain quality of courses there. This one, however, has a lot of bugs (like when I finished week 1, quiz was or may be still is from week 4), quizes are just repetitions of questions from lectures (even answers are the same).

Also, all of the weeks except week 4 is more about programming in python, than NLP. Even the last week assignment is more about writing basic backprop for simple shallow network, than working with embeddings.

Assignments are too easy, splitting every topic in 5 minutes video makes it easier to watch, however I think this format does not allows providing a lot of details on topic, so in the end I feel like this course is to shallow for a 4 week course.