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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: 501 - 525 / 712 レビュー

by Jeeva V


While some of the nuances like how to build word embedding, intuition behind multi-dimension vector transformation logic are not clear or hard to grasp, but am able to understand and familiarize the concept of vector space models with k-nearest, linear regression and naive Bayes algorithms. Very good course material, will pursue the remaining courses and highly recommend to others.

by Christian S


Very nice programming exercises. The grader is quite strict regarding the choice of numpy functions: e.g. array.reshape(-1) is just as good as array.squeeze() but was counted as wrong; v * v is just as good as np.square(v) and was counted as wrong. As a statistician, I also found confusing that you talk about likelihoods but actually you mean likelihood ratios (Bayes factors).

by Artur M


Nice introduction to NLP course. Sometimes I felt that some parts were a bit disconnected (for example, in Week 4 we talk about word translation, but end up not using it). I felt that different pieces were glued together to create the course but some of then didn't match very well. But my overall opinion is that this course is good. You should try it!

by Nikhil M


I am not from a Computer Science background and I am not familiar with python programming. So, the course was a little bit tough for me and took me a considerable amount of time to finish. The teaching was up to the point and very precise. I mostly understood the lectures, and logic to solve the assignments were straightforward.

by Shivam C


The course was overall great. I did learn a lot from the course . It gave me a new way of solving different problems like that of sentiment analysis. The last week was really great where the concepts of translation were taught. I think it could have been better if the concepts of locality-sensitive hashing been more elaborate.

by Rajesh S


Very basic stuff although good for beginners for building the foundation. Programming assignments can be improved further. One is expected to guess and use some pre-defined functions like np.vstack. If you fail to guess what the tutors want and implement something else, no marks are given although the function is correct.

by Damian S


The content and pedagogy of this course is excellent, but there is far too much hand-holding in the programming assignments. I have some doubt whether a person with a passing grade necessarily has mastered that content, or merely is able to carry out step-by-step instructions requiring only basic Python competence.

by José M A I


Buen curso con buenas explicaciones e interesante material práctico. Creo que a veces las explicaciones resultan un poco cortas y en los laboratorios uno está un poco sujeto a usar funciones de Python muy precisas que le restan algo de flexibilidad al momento de hacer la evaluación de la actividad

by Alexander S


Very easy to understand and provides useful techniques I was able to apply immediately. Only downside is the exercises seem a bit on the side of spoon-feeding. The most extreme example being where there's a comment telling us to increment a number by 1, and we literally have to put a 1 there.

by Junior B


The content is really interresting but the programming assignments are not as challenging as they should be. I was expecting more in-depth programming of the mathematical concepts and what we were required to do was just to implement some basic python code around the interresting functions

by Rakshit c


Its well structured course, that builds the foundation in a very simplistic way in its videos and then gives practical implementation using python in exercise. Although there are lot more NLP concepts that are missing in it which I believe will get covered in the remaining specialization

by Apoorv A


It was a fairly good course, but I still expected a bit more from it. The coding assignments could have been improved. rather than making the assignment "fill in the blanks" type, make it more research project oriented. Overall a good exp, learned a few new skills. Thanks!

by Krum A


The course is very good in building intuition of important NLP topics (lectures especially). I would love the labs to include non-numpy tools, otherwise much of the effort goes into figuring numpy out, rather than trying to use the intuition from the lectures in practice.

by Jeroen v H


Quite good - no idea why the one trainer tells us in the videos he is going to teach us something and then the other trainer does all the work. And at the end he comes back to tell us what he taught us - but he did not. All he does is intros and outros of videos.

by Hrushikesh V


Although the course is great, the video lectures could go into more detail regarding how exactly to implement the theoretical concepts taught in python. The lack of this implementation explanation makes the weekly programming assignments unnecessarily difficult.

by David A


G​ood overview, it is quite basic especially if you have previous background on NLP but helps to you have an introductory background of the most basic techniques when treating word embeddings. Eager to keep the specialization to see how complex it would get!

by Saumya G


There could have been more depth added to this course, this would make it more interesting. I liked this course, but on some topics, it seemed more of like we just touched upon and finished. So, adding more insights may be more useful to this course.

by John H


Very well thought out course, great connections between the weeks and everything builds up into real world applications. I am fairly certain there a small number of errors in some math and some of the hero videos would not load for me.

by Gokul G


I was enjoying this course. But last week was not good. In the last week's assignment you have given everything, and have no clue of understanding why when how. I am disappointed because of last week. It was complete waste of time.

by kemal A


Great course on the theory part but the assignments should be more flexible when writing the code, it is just fill in the blanks which restricts you and because of the explicit instructions it is hard to dive in and concentrate.

by J N B P


A really good course that helps you get started in learning Natural Language Processing. It would be very helpful if you're familiar with some basic mathematical concepts of Machine Learning like Sigmoid function, PCA, etc.

by csr y


Lecture is clear and concise. It's good to learn the high-level concepts of basic building blocks and foundation of NLP. However, the online programming exercise has some glitches that needs to be taken care of.

by Ajitesh S


Overall the course was good how ever more intuitions could have been provided on the algorithm part. For example LSH, its short coming while performing sentence similarity tasks should have been discussed.

by Florian C


T​he course gives a good introduction into the basic concepts behind NLP. However, I would have liked to see some more exercises that really challenge you to implement longer sections of code on your own.