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

1,245 ratings
219 reviews

About the Course

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 reviews

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).

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!!

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201 - 220 of 220 Reviews for Natural Language Processing with Probabilistic Models

By Trần T V

Dec 4, 2021

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

By Jinsong T

Jun 8, 2021

T​oo basic and going at too slow a pace

By Esakki p E m

Apr 11, 2021

excellent Material & teaching


Aug 16, 2021

G​ood, very good.

By Randall K

Apr 14, 2021

great course

By MoChuxian

Oct 31, 2020


By Teresa M B

Sep 5, 2021


* 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

By J N B P

Mar 5, 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.

By Amlan C

Sep 17, 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.

By Gent S

Apr 8, 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!

By Aditya J

Aug 14, 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.

By Chi Z

Jan 5, 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

By Tanli H

Dec 21, 2020

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


Jun 6, 2021

Topics were not clearly taught by instructure

By Nemish K

Sep 17, 2020

This was an okay okay course

By Apoorv G

Aug 1, 2020

Not much useful

By P G

Oct 26, 2021

This course is unfortunately a waste of time. The lectures could be compressed into a 60 min video on basics of NLP with probabilistic models and uploaded to YouTube. You will feel initially like you learned a lot of things, yes, but then quickly forget this knowledge as everything is rushed and touched only superficially and you didn't develop solid understanding.

Also, the videos have to be revamped and recorded by someone a bit better in delivering lectures. The lecturer reads a script in a monotone voice and doesn't engage the learner. It feels like sitting through a boring slideshow at work rather than learning SOTA AI stuff from the world's leading tech institution...

This is just my personal opinion, perhaps it will work for you.

By Gennady S

Sep 20, 2020

Too simple. The practical assignment is more not about learning embeddings, but about running about forward and backward pass on the shallow network.

By Abdullah A

Mar 22, 2021

Do not waste your time, these very basic explanations of concepts barely teach you anything.

By Amit S

Apr 18, 2021

Most of the algorithm and logic was implemented beforehand, I did not get to implement much, did not feel good after completing the 2 courses