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Natural Language Processing with Classification and Vector Spaces に戻る による Natural Language Processing with Classification and Vector Spaces の受講者のレビューおよびフィードバック



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....




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.



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


Natural Language Processing with Classification and Vector Spaces: 551 - 575 / 724 レビュー

by Błażej M


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


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


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


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


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


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


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


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


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

by Huziel E S


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


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


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

by Yuhao W


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

by Kirill T


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

by Gianmarcos E


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

by Alberto P


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


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

by Shahin Z


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

by Musa A


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

by Kamal N S


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

by Huynh N A


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

by Nick K


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

by Saúl R


Maybe you could be more rigorous, like in week 1 with the optional derivation of equations

by aydinakgokalp


Course Material needs to be improved. But overall good course and teaches the way for NLP.



Excellent Course that provides detailed insights on usage of NLP and all of its concepts