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    Back to Natural Language Processing with Classification and Vector Spaces

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

    Filled StarFilled StarFilled StarFilled StarHalf Faded Star
    4.6
    stars
    4,553 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 ...
    ...

    Top reviews

    MR

    Feb 12, 2023

    Filled StarFilled StarFilled StarFilled StarFilled Star

    I really enjoy and this course is exactly what I expect. It covers both practical and conceptual aspects greatly and I recommend everyone to enroll in this course to make their NLP foundations strong

    YB

    Oct 16, 2022

    Filled StarFilled StarFilled StarFilled StarFilled Star

    This course is excellent and is well-organized​. I would definitely recommend it to others. The instructor​ explains the topic in a crystal clear way​. I​ learned a lot and had a great time. Thanks!

    Filter by:

    801 - 825 of 900 Reviews for Natural Language Processing with Classification and Vector Spaces

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    By Tanmay R S

    •

    Oct 22, 2022

    not enogh explanation of topics ... please give in detail explanation of topic . It seems like after this course i need to do few more courses on the same topic cause it just introduces to the concepts and not giving in depth knowledge like other courses of andrew ng.

    Filled StarFilled StarFilled StarStarStar

    By Christopher M

    •

    Aug 3, 2023

    Great information but not enough opportunities to practice skills or internalize concepts. The assignments are too easy and don't let you flex much brain power. I feel like the lack of any repetition will result in almost immediately forgetting material.

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    By James M

    •

    Nov 6, 2021

    I feel like feed back and testing of your code code be more detailed to help pin point coding mistakes. I was spinning my wheels at the end and did see any solutions or discussions on my issues. I still passed but would like to see what I did wrong.

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    By Phước T V

    •

    Sep 12, 2021

    The lecture videos are a little short but provide some fundamental insights. It would be better if the videos were longer and more detailed or some supplemental resources. Overall a good course if you are a beginner or don't know where to start.

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    By Sherali O

    •

    Dec 25, 2020

    Shallow explanation in some topics in the lectures. It would be great if lecturer explained topics in more detail, and answer questions like why we use this model, show how it was created, pros and cons, and show why it works using math proofs.

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    By Espoir M

    •

    Sep 15, 2020

    I like the way the course use simple machine learning technic to solve a complicated problem,

    for someone who likes mathematic a lot could be done in explaining mathematic concepts,

    the assignment could be improved by using unit testing.

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    By Gianpaolo M

    •

    Jun 24, 2021

    Andrew, come back with us!

    Although very interesting, the course spend too many time and many student efforts in details like PCA and LSH. This is a good way to loss the big picture during the course.

    Filled StarFilled StarFilled StarStarStar

    By Sina M

    •

    May 14, 2023

    Compared to prior deepLearning Ai courses. the lecturers were very robotic and un natural. The explanations were much less clear and less effort was made to explain the intuitons behind formulas.

    Filled StarFilled StarFilled StarStarStar

    By shaider s

    •

    Dec 20, 2020

    Lectures were very straightforward and digestible, however the assignments had inconsistencies within themselves, especially between the written instructions and the comments in the code cells.

    Filled StarFilled StarFilled StarStarStar

    By Benjamin W

    •

    Jul 19, 2024

    Interesting, but surprisingly many quality issues. Some topics, such as naive Bayes classification, need a better motivation (explain intuition and connection with Bayes theorem first).

    Filled StarFilled StarFilled StarStarStar

    By Bogomil K

    •

    Jul 27, 2021

    The topics were interesting overall and the lectures even though rather short were still rather informative. Too much focus on specificities of libraries and frameworks in the exams.

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    By Hamman S

    •

    Jan 13, 2021

    While this was a great introductory course to some of the basic tenets in NLP, various ancedotal examples were too convoluted to be useful in gaining an intuitive understanding

    Filled StarFilled StarFilled StarStarStar

    By Mansi A

    •

    Aug 23, 2020

    This course provides you with a good but basic start to the world of NLP. Week 4 LSH and Hashing should be explained more clearly. Assignments are not challenging.

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    By N N

    •

    Oct 7, 2020

    Basically lecturers' delivery is not so good that you could get distracted easily.

    Often, a video contents and a jupyter notebook don't match to each other.

    Filled StarFilled StarFilled StarStarStar

    By PRANSHU K

    •

    Sep 14, 2020

    Seemed easy to me. Rest all is good, the explanation and assignments.

    I am reducing star by one rating because of the interface for assignment is poor.

    Filled StarFilled StarFilled StarStarStar

    By Michele V

    •

    Sep 17, 2020

    Good coding part. For my background the lecture material was a bit too easy. However, if your intention was to keep it easy, then good job!

    Filled StarFilled StarFilled StarStarStar

    By Yuthika B

    •

    Nov 30, 2022

    The course misses depth and needs to focus on applications of these algorithms rather than introducing more and more algorithms so fast.

    Filled StarFilled StarFilled StarStarStar

    By Sebastian J

    •

    Mar 26, 2024

    The videos were too short to properly explain things and the notes sections after each were basically just screenshots of the video.

    Filled StarFilled StarFilled StarStarStar

    By Toon P

    •

    Jun 7, 2022

    It is rather annoying that the videos are short and even shorter because half of the time is spend on an intro and outro

    Filled StarFilled StarFilled StarStarStar

    By Diana G

    •

    Apr 30, 2024

    The course has been beneficial, but it could greatly benefit from more thorough explanations of mathematical concepts.

    Filled StarFilled StarFilled StarStarStar

    By Leonardo F

    •

    May 24, 2021

    Liked the in-depth linear algebra and gradient descent, but missed some extras like lemmatization and HMMs in NLP...

    Filled StarFilled StarFilled StarStarStar

    By Anatoly D

    •

    Aug 4, 2021

    Compared to other deeplearning.ai courses (esp. Adrew Ngs) very low in-depth explanations and challenge level.

    Filled StarFilled StarFilled StarStarStar

    By AG S

    •

    Aug 20, 2020

    Although the course presents an overview of the topic, I was expecting a more advanced and deeper approach.

    Filled StarFilled StarFilled StarStarStar

    By Harsh G

    •

    Feb 23, 2021

    Didn't Feel Like I am learning some concept very basic concepts nothing related to real life and NLP

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