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Natural Language Processing with Classification and Vector Spaces に戻る

deeplearning.ai 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

4.6
3,407件の評価
691件のレビュー

コースについて

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....

人気のレビュー

MN

2021年5月24日

Great Course,\n\nVery 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

SK

2020年7月17日

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.

フィルター:

Natural Language Processing with Classification and Vector Spaces: 651 - 675 / 704 レビュー

by Harsh G

2021年2月23日

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

by Susie B

2021年10月15日

In general, good. M​isspellings in assignments is not very professional, should be revised.

by Phillip

2020年9月20日

Would be good if there are more checkpoints to see if the codes are correct or not.

by Kestin C

2020年10月29日

Some example is hard to understand, and few of the diagram is ambiguous.

by Alex A

2020年12月21日

Especially later excercises contain code/instructions that are unclear

by Luiz O V B O

2021年6月24日

I would like to have more content and explanation about the math

by john s

2021年1月10日

I don't feel the assignments help understand the material.

by Huang J

2020年12月23日

The videos are too short. Discussions are oversimplified.

by Renato G

2021年12月14日

It is an interesting course to learn the basics of NLP

by Anish S

2020年11月9日

good for beginners, but needs more advanced concepts.

by Sonam G

2020年8月2日

The explanations in the videos could be improved.

by Deleted A

2020年6月27日

No longer required. Beyond my present knowledge.

by Shayan J

2020年12月26日

Content is verbose and locks context in places

by Lorena P

2021年2月14日

I believe that explanations where too shallow

by Zaid A

2021年12月11日

v​ery good course, a lot of stat and math

by Sihao L

2020年8月18日

So many small mistakes here and there

by Harshita B

2020年12月4日

I didn't quite get the feel of it

by Spandan.Pandey B

2022年3月27日

Problems in week 3 Assignment

by jkf

2020年10月14日

Just ignore the video!

by Rishik R

2021年4月5日

Too easy

by Dmitriy I

2021年1月28日

Too easy

by Christoph H

2020年9月3日

I believe the course does not allow you to study NLP in depth. Compared to the deep learning specialisation by deeplearning.ai, this course has probably hours(!) of video material less. PCA is for instance presented in ~4 minutes and the lecturer concludes with "now that you know all about PCA". The only further reference provided is a link to the standard textbook in the field, no detailed study guide or references for individual topics. Excercises are done in notebooks and test beginner python skills instead of nlp understanding (Basically: "Look up key i in dictionary j and store vector k"). It does do a good job in giving an overview about NLP.

by Andreas B

2020年9月8日

I was torn between two and three stars. Two, as mathematics are dealt with far to shallow. No proofs, no motivation, nothing. And in the final week, there is a massive notebooks with a lot of flaws and a lot of cells you have to code in a specific, sometime suboptimal, way. Otherwise, the grader will throw errors. All in all, things are handled to shallow and it is more of a coding lesson than a deep dive into ML, which necessarily requires mathematics. This is one more of those "Become a data scientist without mathematics" things the world does not need.

by Shawn

2022年1月29日

lectures are pretty mediocure. basically it lacks motivation behind algorithms, you are simply told what to do, really like "machine" learning

you'll spend a lot of time in the assignment, not focusing on implementing your algorithm, but adjusting incorrect input or output format that passes all tests but fail the final grading for some reason (also in week 3 the assignment has one or two questions that do not even tell you what's the input data and you have to "print" them to get an idea lol)

by Jorge E P C

2021年2月3日

The lectures skip over important features that should be explained in more detail. Other important concepts are left to the labs, even if those require a good explanation. Evaluations are not a help to practice or understand concepts. Most of the time spent on evaluations is figuring out how to do things in Python rather than follow the concepts. People can obtain 100% in the evaluations but learn nothing. It is indeed a very poor course.