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

4.7
stars
1,201 ratings
210 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!!

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201 - 210 of 210 Reviews for Natural Language Processing with Probabilistic Models

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.

By DHRUV M

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 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