Natural Language Processing

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Below are the top discussions from Reddit that mention this online Coursera course from National Research University Higher School of Economics.

This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few.

Chatterbot Tensorflow Deep Learning Natural Language Processing

Next cohort starts July 13. Accessible for free. Completion certificates are offered.

Affiliate disclosure: Please use the blue and green buttons to visit Coursera if you plan on enrolling in a course. Commissions Reddsera receives from using these links will keep this site online and ad-free. Reddsera will not receive commissions if you only use course links found in the below Reddit discussions.

Taught by
Anna Potapenko
and 4 more instructors

Offered by
National Research University Higher School of Economics

Reddit Posts and Comments

0 posts • 9 mentions • top 9 shown below

r/learnmachinelearning • post
17 points • xord37
What are the best resources for learning NLP?


What do you think are the best resources for learning NLP (as for now)?

Please don't say the stanford course because it doesn't teach it well enough.

Python is the preferred language and if you have an experience or know some course that you think is really good, I would be glad to hear about that (I don't care if it's free or not).


So far, I thought of being enrolled in these ones:


Anyway, what do you think?

r/LanguageTechnology • comment
2 points • lambdaofgod

There's only one Coursera NLP course for now...

r/OMSCS • comment
2 points • slimydude

This is one that's part of a specialization I've seen recommended

r/computerscience • post
21 points • RGnt
Planning a course list for undergraduate self study 'degree', and would like your input.

Hello, yet another one planning on Bachelors level studies online with heavy emphasis on machine learning and data science, i've been trying to put together a list of courses for my self to complete (and get a fancy certificate for completed courses) using coursera. So far I've come up with following list:

Learn to Program: The Fundamentals and Learn to Program: Crafting Quality Code (University of Toronto - / )

Introduction to Discrete Mathematics of Computer Science (University of California, Sand Diego High School of Economics - )

Data Science Math Skills (Duke University - ) Introduction to Logic (Standford University - )

Data Structures and Algorithms (University of California, San Diego, High School of Economics - )

Fundamentals of Computing (Rice University - )

Machine Learning (Stanford University - )

Deep Learning ( - )

Software Design and Architecture Specialization (University of Alberta - )

Natural Language Processing (High School of Economics - )

Data Science Specialization - (John Hopkins University -

When it comes to math, physics and possibly electrical engineering I've considered relying purely on khanacademy to fill in the gaps I have at moment.

So here's the main question, is there something you guys/gals can see that is "wrong", is there something that's missing or just would be nice to add on top of that?

Any comments/critique/your opinions are most welcome!

r/brasil • comment
1 points • soldcron

"Repositório" dos melhores papers da área:

Esse curso de NLP é maravilhoso. Ótima introdução:

r/LanguageTechnology • comment
1 points • lambdaofgod

If you know some deep learning/ML I'd argue that Coursera's NLP Course is the best choice. If you don't know DL you can also do previous courses from this specialization.

If you're looking for overview of text summarization methods (most are from 90s and 00s) check out Dragomir Radev's lectures. Also learn what is extractive vs abstractive summarization.

For summarization in Python gensim is your best shot (it has TextRank, probably most widely used summarization method). It's pretty slow, but it has lots of examples. If you're interested in something different you can check out this centroid-based summarization method (disclaimer - I'm a contributor).

Note that the above methods are unsupervised and require hardly any training. Abstractive summarization is much harder and it is more domain-specific since you need to train a language model. It's also much harder to use - current implementations wrap deep learning frameworks, and I haven't seen anything that is straightforward to use as extractive methods I mentioned above.

r/LanguageTechnology • post
1 points • Proxify
I'm starting to get more into NLP can you guys recommend me what I could look into?

I am going through the Stanford lecture for CS231n which I know is not for NLP but I feel it gives me some useful knowledge overall.


Additionally I was looking at a coursera course for NLP but I have found I can't quite follow yet, mostly because I don't enjoy the teaching style so I end up spacing out. Can you guys provide me with some places I could start into this myself?


I also was thinking of opting into either AWS or GCE but I am unsure if 1) I should right now, and 2) which one would be more beneficial for me. Any insight into that would also be useful please.

r/LanguageTechnology • comment
1 points • stepthom
r/NLP • post
1 points • ai-lover
16 Free Natural Language Processing Courses

1.Speech and Language Processing by Dan Jurafsky and James Martin

2. Deep Learning for Natural Language Processing by Richard Socher (Stanford University)

3. Natural Language Processing (NLP) by Microsoft

4.Andrew Ng’s course on Machine Learning

  1. The video lectures and resources for Stanford’s Natural Language Processing with Deep Learning

6. Sequence Models for Time Series and Natural Language Processing 

7. Deep Natural Language Processing course offered in Hilary Term 2017 at the University of Oxford.

8. Natural Language Processing Fundamentals in Python by Datacamp

9 Natural Language Processing by Higher School of Economics

10 How to Build a Chatbot Without Coding by IBM

11. CS 388: Natural Language Processing by University of Texas

12. Natural Language Processing with Python

13. CSEP 517: Natural Language Processing by University of Washington

14. Dan Jurafsky & Chris Manning: Natural Language Processing

15. NATURAL LANGUAGE PROCESSING by Carnegie Mellon University

16. CS224n: Natural Language Processing with Deep Learning by Stanford University


The above list is taken from