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

4.7
stars
1,658 ratings

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

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!!

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276 - 286 of 286 Reviews for Natural Language Processing with Probabilistic Models

By Tanli H

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Dec 21, 2020

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

By DHRUV M

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Jun 6, 2021

Topics were not clearly taught by instructure

By Nemish K

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Sep 17, 2020

This was an okay okay course

By Amitrajit B

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Mar 4, 2022

Doubt support can be better

By Apoorv G

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Aug 1, 2020

Not much useful

By Darren

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Jan 21, 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.

By Gennady S

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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 Sergio B

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Dec 15, 2022

I think that model evaluation and test could be covered better

By Amit S

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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

By Arun K

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Dec 30, 2023

Even YouTube has better content on this topic

By khubaib A

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Dec 8, 2022

Just a stupid course