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

1,219 ratings
213 reviews

About the Course

In Course 2 of the Natural Language Processing Specialization, offered by, 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

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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51 - 75 of 214 Reviews for Natural Language Processing with Probabilistic Models

By Jian G

Oct 27, 2020

this course is well-designed. It incorporates all factors that make a successful online course. bitesize video, easy to understand, exercise notebooks, etc.

By bob n

Feb 13, 2021

Nicely broken into digestible chunks. Labs well done, not too easy, and too too frustrating. Material presented clearly and in (again) nice small steps.

By ps

May 30, 2021

I'm really thankful to the professors for sharing there knowledge and experience and creating this excellent course. I have learnt a a lot. Thank You !!!

By Abanoub Y

Dec 28, 2020

A great course in the very spirit of the original Andrew Ng's ML course with lots of details and explanations of fundamental approaches and techniques.

By Ivan V S

Sep 26, 2021

I​ grade 5 stars, but take in account, that this course is very specific. It provides real basics of NN and NLP and it is more fundamental than apply.

By Baurjan S

Aug 29, 2020

Totally enjoyed it. I took a Deep Learning course a couple of years ago and in some respect, it was a great refreshment form two years ago. Thank you!

By Aanand

Feb 3, 2021

Course well structured. SBOW very well explained and registered firmly. Word embeddings explained very well. Overall very happy from the learning’s

By Long H T

Jun 14, 2021

This course is amazing! I could not know that I can learn so many interesting things! I am so happy to take the next course in the specialization.

By Alex M

Jan 7, 2021

Es extenso, pero super interesante la forma de aprender por coursera, cbow model es super chevere. aprendí también, temas de toquenizar textos.

By Ankur G

Sep 26, 2020

More fun if it would have more ungraded coding problem to solve ,It would be optional so that who wants to do more practice can be benefitted.

By Hieu D T

Apr 21, 2021

Very well built lectures. The content is foundational enough for new student like me. I feel more comfortable with keywords in this field now.

By Russell H

Aug 18, 2020

A bit light on the math vs. some other ML courses I have taken, but the good news is that this lets the focus be on the NLP-specific material.

By Kartik S

Sep 6, 2020

The course content was really engaging. This really helped in understanding many of the basic foundational models for pivotal tasks of NLP.

By Prakhar M

Nov 10, 2020

Very intresting and effective way of studing NLP . Totally amazing and 10/10 for the clearity of lecture delivery and video presentation .

By Anshul B

Mar 7, 2021

I liked this better than the 1st course in the specialization. Instructors cover some real fundamental concepts and techniques in NLP

By Vedika P

Oct 19, 2020

Brilliant course. Very enriching content and so very well explained. Challenging assignments made me explore each concept in-depth.


Sep 10, 2020

Excellent course, although the last assignment is very straight-forward and may be good to have a more in depth coding of the loss.

By Prateek J

Feb 4, 2021

Amazing course. Starts from the basics and then teaches concepts in-depth. The exercises are also very elaborate and well thought.

By Moustafa S

Sep 8, 2020

now we are talking, i really enjoyed this one, this gives you a pass to the first course as i didn't enjoy it at all :D, good job!

By RAJ B S 1

Sep 6, 2020

Amazing how you make it look so so easy and explain straight to the point. Loved the implementation details and the notebooks

By Jayantha N

Aug 7, 2020

All my doubts about word2vec models were cleared, after taking up this course. The instructor's diction was easy to follow.

By Aftab K

Jan 18, 2021

Very well presented with the right level of detail and emphasis along with complementary programming exercises.

By Bernard E

Oct 14, 2020

Great coding examples and exercises! All functions coded from scratch, no ML libraries used, which is great.

By Thomas L

Feb 16, 2021

Exceptional. Second only to Andrew's course. The coding assignment's were the perfect level of difficulty.

By Dustin V

Jan 16, 2021

Excellent primer material for probablistic NLP approaches. Sets the foundation for deep learning with NLP