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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,\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


Natural Language Processing with Classification and Vector Spaces: 51 - 75 / 672 レビュー

by Achkan S


This course has too many problems as it stands:

1) They haven't chosen an audience: the concept that they explain are trivial for anyone having (even basic) machine learning (or even basic linear algebra) knowledge. However, it doesn't meant that this explanations would be useful for beginners: they are too short and incomplete (the "videos" are on average 3 minutes long!!) and what they focus on is often not the most relevant part.

2) There is no reading material: no books, no papers, no theory. It wouldn't be a problem if the videos themselves were decent, but most of them are about 1 minute long. You can't explain machine learning in such a short time.

3) The code of the assignments, especially assignment 4, is unclean (e.g. unused variables) and contains minor bugs.

4) The script that grades the assignments has very strict requirements: as an example, very often, if you use instead of np(x,A), then it complains and says you've failed. This happens for a lot of numpy functions, and it makes the process of submitting results tedious.

5) Again, regarding the course material itself, many of the key aspects are not discussed. For example, word embeddings are given that have some nice properties, but its never explained how they have been obtained.

Overall, it seems completely rushed.

by Harish A


Poor quality of video content

Persistent issues in accessing the labs (It hangs 50% of time)

by Yuri C


I enjoyed the course very much! I would say, there is still some things to improve, like the treatment of the implementation of the hash-local search, or some typos here and there along the way in the notebooks. Another suggestion is to postpone the implementation of SGD until after you get some warm-up in numpy during week 2-3. All in all I quite enjoyed the approach to be able to build the tools myself with numpy. This way, it demystifies the use of pre-built packages and lets the learner indeed understand what is going on under the hood. Of course, there is always a trade-off between being precise and being easy to understand. I think nevertheless that this course is spon-on in this trade-off optimization task. ;)

by Akshay M


This is an amazing course for beginners in the field of natural language processing. It starts with the very basics of machine learning and natural language processing. Exploring sentiment analysis using two different approaches one is a frequency-based approach (involving logistic regression) and the other is a probabilistic approach (involving naive Bayes approach). This course also gives a glance of vector spaces and techniques to convert multidimensional data to lesser dimension data using approaches like PCA. I learnt new topics like locality sensitive hashing during the last week of the course. It was a fun and engaging course overall :)

by Kritika M


I really like the way the course is structured and the way it is taught. The language is clear and it goes at a good pace. I have completed the Deep Learning Specialization as well and felt that this course had a better segregation of material/videos. The short videos make sure you don't lose focus or get bored. Content-wise, the course is great for understanding the initial steps required for approaching NLP problems. Highly recommend it and I look forward to completing rest of the courses in this specialization.

by Orson T M


No matter who you are or who you have been, you can be whoever you want thanks to this course you will understand in great detail the Natural Language Processing with Classification and Vector Spaces. The teacher rigorously explains its content by putting you in a real situation and the key concepts are very well explained in clear the academic rigor is there now I can affirm without reserve that I understand very well several concepts which were strange for me thank you to coursera and

by John A J


This course had helped me become familiar in natural language processing. Before taking the course, I feel that NLP is already like a plug-and-play thing due to deep learning. However, it had helped me understand the importance of preprocessing especially to get the right embedding. Additionally, it also help me understand a glimpse of doing sentiment analysis and Machine translation. Indeed, I still have many things to learn but this course is a great way to be introduced on the NLP.

by Mikolaj O


Great intro to the world of NLP. For those with a background in python, linear algebra and statistics (my case) course will take significantly less time, as you can skip some of the videos and rush through easier notebooks. Assignments will make sure you haven't overlooked parts you don't yet understand. In my opinion comments and hints sometimes lead by the hand a little bit too much, but maybe I'll change my mind when faced with assignments from next courses of the specialisation.

by Pramod


I had attempted other NLP coursse before attempting this course. I found this course is a good to people who are new to NLP or even new to machine language. The hand-on examples and assignments are the plus points of this course. Though the coding the assignment may look like "fill in the blanks" sort of exercise, I appreciate it since it helped me to understand the concepts. Planing to take up the next course in this series. Great instructors and program is well structured.

by Marcio R


Amazing course overall, I have a few years of experience working as Data Scientist and still could get many valueble learnings from it. So whether you are a beginner or someone with some experience I would recommend it. The material is great, the Notebooks used for coding are very well structured, the lessons are very focused - I recommending doing some searches on the side to make sure you grasp all the concepts properly. Also the Slack community is very supportive.

by Yusuf C A


I had an project about NLP and I was trying to find a course on internet. To be honest I tried another website's course but it didn't help so much. When I see that the videos are really short in this course I started to think like "What, is this joke? Will I really learn anything?". However I understand that courses teach so many things. I'm really glad to get this course and I believe that it has given me a lot for my future career.

by Pietro B


I've done online courses before, including other deep learning courses. But I can't talk enough about how well organized and just far superior the courses are. The video lessons are short and to the point, the exercise sessions are challenging but not impossible, and the community of students and teachers are all very active on the message boards to help you get through when you are stuck. Can't wait to do the rest!

by Grant H


Andrew Ng and his colleagues have delivered another excellent course - these really set the standard for online courses on machine learning. The concepts and coding are explained very clearly by the tutors, and the exercises offer a suitable level of challenge. The final assignment involves building an automated translation capability based on word vectorisation and hash tables, ie a potentially useful/usable capability.

by David M


The course is very well prepared and the assigments are really useful to understand the complexity about some of the concepts that are explained along the course. I strongly recommend this course to anyone interested in NLP it does not matter whether you have too many expertise in this specific field. Of course, having some knowledge about Machine learning, statistical modelling or any AI related-insight will be a plus.

by 沈建军


The course does not teach me the NLP basic knowledge, it also help python beginner learning avoid mistakes. The course is well designed, I learning a lot though I already know the space vector and etc. I .

I sincerely thank for the team made this wonderful course! I fully believe e-learning will bring equalityto the all students on earth, especially to computer student. Because many things could learn from remote.

by Igor D A


It was a wonderful experience. I learned a lot, I enhanced my knowledge on python, vectors and NLP. I also learned with my colleges in forums and Slack channels. I am sure that the knowledge I have acquired here I will be able to apply in my work and projects with NLP models. Thank Coursera, and Stanford to bring that course. Thank to the professors Younes Mouri, Lukazs Kaiser and Eddy Shyu.

by Yixuan Z


Wonderful! And I really love you add an feasible code and explanation of how to implement the experiment on my local computer. I also like you mentioned you stored some function in utils file, so I could also learn how to write this function by myself in order to run model on my own dataset! Thank you so much! This course is amazing!! I would definitely recommend this course to my colleague and friends!

by Ahungwa G


Before now, I was made to understand that NLP was pretty complex, maths-heavy, and difficult to comprehend. But the manner in which the instructors excellently broke-down the concepts and explained them with clarity makes me feel the opposite. THANKS A LOT for the awesome delivery. I recommend this course without any reservation. Can't wait to continue with the other courses in the specialization.

by Sandu I C


This is a perfect introduction! I have a fairly good mathematical background, some experience with data science and I was looking for a brief introduction to NLP. I enjoyed the presentation, the selected information and the applications. I also appreciated the mathematical details of some concepts and the high degree of applicability. You can start using the information/the code right away.

by Gergana G


A very insightful course. The assignments are well thought and suiting the material, the great automatic grading provides fast results and enough feedback to move ahead. There are more than enough explanations and comments on the provided code, making it easy to understand the concepts and become comfortable with mathematical notations and the theory behind the algorhtms.

by Dylan T


Great content. This course is excellent for anyone who is learning some of the fundamentals of NLP. However, if you have foundational knowledge in machine learning, this course will likely only serve as a refresher. I'm taking this course as part of the specialization with the expectation that the other courses will cover advanced concepts and state-of-the-art techniques.

by Anuar M


The material given in this course is very straightforward and easy to understand. Although only the basics of NLP are covered in this course, the knowledge gained in this course can be implemented in more advanced techniques of NLP. I would like to thank instructors for good explanation and the assignment developers for great usability of readable code and autograder.

by Mohana P


Really good content. Short, but very informative videos : perfect for people who can't dedicate a lot of time to the course. The format of the assignments is very beginner friendly(which is a good thing) but i wish the assignments were more full-on coding exercises, rather than filling in the blanks. Overall a perfect course for people getting into NLP!

by Soo J K


I enjoyed this first part of the course. It slowly walks you through with lots of hands-on coding practice opportunities - just what I wanted. Also the Slack channel helps tremendously. Mentors or fellow students, they are willing to reply to your questions. I'm so happy to finish course and receive the certificate. Moving to the second part now! :D

by Francois R


Excellent Course

I really appreciated that it was built as a sort of continuation of the Excellent Deep Learning Specialization from

In particular, I mean that the important intuitions are well explained.

I also liked that the final assignments for each week provided a kind of base material for more our personal projects.

Thanks a lot.