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Learner Reviews & Feedback for Natural Language Processing with Classification and Vector Spaces by DeepLearning.AI

4.6
stars
4,275 ratings

About the Course

In Course 1 of the Natural Language Processing Specialization, you will: a) Perform sentiment analysis of tweets using logistic regression and then naïve Bayes, b) Use vector space models to discover relationships between words and use PCA to reduce the dimensionality of the vector space and visualize those relationships, and c) Write a simple English to French translation algorithm using pre-computed word embeddings and locality-sensitive hashing to relate words via approximate k-nearest neighbor search. 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

SJ

Jul 17, 2020

One of the best introductions to the fundamentals of NLP. It's not just deep learning, fundamentals are really important to know how things evolved over time. Literally the best NLP introduction ever.

MN

May 24, 2021

Great Course,

Very few courses where Algorithms like Knn, Logistic Regression, Naives Baye are implemented right from Scratch . and also it gives you thorough understanding of numpy and matplot.lib

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651 - 675 of 851 Reviews for Natural Language Processing with Classification and Vector Spaces

By Błażej M

Sep 10, 2020

Great course! What I'd really like to see more is how the embedding database is build (it was mentioned how it might be done but there was no exact explanation)

By Brian M

Sep 14, 2020

Videos were very basic (and short), but the workshops and assignments were thorough yet well commented (in code) allowing for quick progress and learning.

By Ravi V K

Jul 20, 2020

I loved it overall! here are some considers...some more video explanations and references would have made this more interactive and game changer

By Swapnadeep S

Jul 17, 2020

Its an awesome course, but it would be nicer if students can learn to code on practical projects instead of writing everything just from scratch

By Akshay S

Aug 14, 2021

Nice content and easy explanation. There are a few mistakes in the programming assignments which should be corrected. Overall liked the course!

By Andrea D

Oct 5, 2021

Exceptionally well conduceted course, but I got to say that the last two weeks are weaker than the first two in terms of depth of explanation.

By Andrés M C

May 18, 2021

The way the course is evaluated could be different, because it is too literal and sometimes you get to the same answer doing different things.

By Randall K

Apr 2, 2021

I thought the HW was a bit too easy. I understand this is MOOC, but perhaps some optional assignments that don't have as much templated code.

By vijaya k e

Jan 16, 2022

Overall, the course is good. But, the last assignment of using KNN means with LSH is a bit difficult to understand. That needs improvemnt.

By Huziel E S F

Aug 13, 2021

In general good. The only problem was that some notebooks have typos, which makes the exercises a bit confusing. In particular in week 4.

By Abhinav G

Aug 7, 2020

The course content was well planned and assignments were good. But due to several errors in videos and grader issues, giving a star less.

By Vincent H

Dec 31, 2021

Course content is good, however, there are a number of bugs and errors in the quizzes and assignments that may throw people off.

By Sharthak G

Aug 6, 2023

I think the intuition for PCA should have been expanded a bit more, but overall a very good introduction to the specialization.

By Fabio

Oct 26, 2022

Great course, but it will be better if the instructors add a few more practical examples and explain a bit more the topics.

By Yuhao W

Aug 16, 2020

Last section LSH is a bit difficult, please add more details and extend current videos length to make LSH understood better.

By Kirill T

Jul 11, 2020

There were some unexplained moments (like PCA implementation in the 3rd course), but overall the course seems good.

By Gianmarcos E

Nov 26, 2020

Me ayudó mucho este curso para entender como programar en python enfocandome al procesamiento del lenguaje natural

By Anthony W

Jun 26, 2023

The final week of the course is not necessary (can be set as optional), since it's not commonly used in industry.

By Alberto P

Mar 12, 2022

There were some files in the assigments that had a lot of bugs. But the rest of the course was very good.

By Vaibhav O

Jul 3, 2020

Some of the concepts are too basic in the course and proper emphasis on vectorized operations is lacking.

By Shahin Z

Oct 7, 2020

Very nice. (Would be even better if you can iron out all the little typos in the labs/assignments.)

By Musa A

Jul 1, 2020

Course content was OK, but the instructer's performance is below average. I am sorry to say that.

By Kamal N S

Sep 29, 2020

Informative course. Notebooks are well explained and very helpful to learn many concepts of ML.

By Huynh N A

May 17, 2021

lab and assignments should be to understand and practice the theories, not programming skills

By Mikalai K

Jul 29, 2020

good one! I would have done more complex tasks as assignments. Rather than that - very nice!