Chevron Left
Back to Natural Language Processing with Probabilistic Models

Learner Reviews & Feedback for Natural Language Processing with Probabilistic Models by DeepLearning.AI

4.7
stars
1,218 ratings
213 reviews

About the Course

In Course 2 of the Natural Language Processing Specialization, offered by deeplearning.ai, 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 important 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. Please make sure that you’re comfortable programming in Python and have a basic knowledge of machine learning, matrix multiplications, and conditional probability. 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 reviews

NM
Dec 12, 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
Dec 2, 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!!

Filter by:

151 - 175 of 213 Reviews for Natural Language Processing with Probabilistic Models

By Saoudi H

Aug 24, 2020

sooo goooood ^_^

By Nguyen T D

Sep 22, 2020

That's great!!!

By Saurabh S

Apr 11, 2021

Awesome course

By Gonzalo A M

Jan 6, 2021

Great Course!!

By Sudharsan

Jul 20, 2020

Awesome course

By Mohammad B A

Nov 11, 2020

I am so happy

By Md. S C

Sep 21, 2020

clear concept

By Anurag S

Oct 11, 2020

Great course

By Reji C J

Aug 16, 2020

Nice Course

By Mohamed S

Oct 10, 2020

I loved it

By M n n

Nov 15, 2020

Good One

By Zoizou A

Oct 25, 2020

amazing

By THIRUKARTHIKA M

Jul 17, 2020

awesome

By Venkatasai A

Apr 2, 2021

keeeka

By Ricardo F

Jan 18, 2021

Great!

By Jeff D

Nov 10, 2020

Thanks

By Darwin P C M

Sep 13, 2020

Thanks

By 克軒廖

Feb 9, 2021

Nice!

By Rifat R

Aug 2, 2020

Best.

By Chamoda J

Aug 2, 2020

great

By Thành H Đ T

Oct 17, 2021

đỉnh

By MOURAD B

Apr 18, 2021

good

By D. R

Mar 22, 2021

I'm a master/graduate student who took an NLP course in Uni.

I think that overall this is a very a good introduction to the topic. Some concepts are really well explained - in a simple manner and with a lot of jupyter-lab code to experiment with.

In general in this specialization - the first 3 courses are good. There are some quirks (e.g. why Lukas is needed at all? He doesn't really teaches, just passes it on to Younes) but nevertheless I learned from it. And I think they have good value in them.

The 4th one, however, is completely disappointing. First 2 "weeks" are confusing, not really well explained, but somewhat "bearable". The last 2 weeks are complete sham. They claim to teach "BERT" and "T5" but don't really give any value. You're better off going elsewhere to learn these concepts.

If it wasn't for this, I would give the overall experience a 5 stars, but because of this, I think the overall is more like 3 or 4.

By Eloy S

Jun 29, 2021

Es bastante completo, y en general, claro; salvo un detalle: explica demasiado superficialmente PCA, pero luego para la tarea hay que implementarlo manualmente. También tiene algunos bugs desde hace meses a pesar de haber sido reportados con solución. Además, las lecturas posteriores a los videos a veces son escuetas y le hacen falta algunos diagramas que se ven en el video (conviene sacar capturas de los videos para tomar nota).

It is quite complete, and generally speaking very clear, except PCA: it's covered only superficially but it is required to implement by hand on the assignment. Also it has some unsolved bugs since several months ago, despite they were reported with solutions. Also, the readings after the videos are sometimes narrow and lack of some diagrams shown on the videos (it is useful to take screenshots to take notes).

By Nima M

Nov 6, 2020

The content of the course was really interesting an engaging. But the assignments mostly only helped in understanding the details of the algorithms and processes. It would have been nice to get to learn how to use state of the art libraries, which would've been more practical. Although, in fairness, anybody who completes this course should be able to make use of off-the-shelf libraries. Another point was that when the instructor was narrating the slides, his intonation was occasionally a bit off, making me lose track of the subject and having to re-listen few times.