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Bewertung und Feedback des Lernenden für Natural Language Processing with Probabilistic Models von

1,357 Bewertungen
239 Bewertungen

Über den Kurs

In Course 2 of the Natural Language Processing Specialization, you will: a) Create a simple auto-correct algorithm using minimum edit distance and dynamic programming, b) Apply the Viterbi Algorithm for part-of-speech (POS) tagging, which is vital for computational linguistics, c) Write a better auto-complete algorithm using an N-gram language model, and d) Write your own Word2Vec model that uses a neural network to compute word embeddings using a continuous bag-of-words model. 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....



12. Dez. 2020

A truly great course, focuses on the details you need, at a good pace, building up the foundations needed before relying more heavily on libraries an abstractions (which I assume will follow).


2. Dez. 2020

A neatly organized course introducing the students to basics of Processing text data, learning word embedding and most importantly on how to interpret the word embedding. Great Job!!

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51 - 75 von 240 Bewertungen für Natural Language Processing with Probabilistic Models

von Harshavardhan S

3. Dez. 2020

A neatly organized course introducing the students to basics of Processing text data, learning word embedding and most importantly on how to interpret the word embedding. Great Job!!

von Sazzadur R

4. Aug. 2021

Another great course introducing the probabilistic modelling concepts and slowly getting to the direction of computing neural networks. One must learn in detail how embedding works.

von Aniruddha S H

29. Sep. 2020

Very good course! helped me clearly learn about Autocorrect, edit distance, Markov chains, n grams, perplexity, backoff, interpolation, word embeddings, CBOW. This was very helpful!

von Bharathi k N

11. Sep. 2020

This is one of the best courses i have taken. I have learned a lot from this course. Assignments were great and challenging. Thank you team for this amazing course.

von Aditya h

9. Okt. 2020

Thoroughly relished this course. Each and every concept is explained in depth as well as there is a companion notebook to explain as well as practically implement the concepts.

von Kazuomi K

1. Juli 2020

This course is very good introduction to NLP Probabilistic models such as Hidden Markov model, N-Gram Language model, and Word2Vec with Python programming assignments.

von MARC G

24. Jan. 2022

Excellent course! Well designed and taught. I would have liked more advices on how to preprocess text before applying word embeddings (lemmatization, stemming, etc.)

von Jian G

27. Okt. 2020

this course is well-designed. It incorporates all factors that make a successful online course. bitesize video, easy to understand, exercise notebooks, etc.

von bob n

13. Feb. 2021

Nicely broken into digestible chunks. Labs well done, not too easy, and too too frustrating. Material presented clearly and in (again) nice small steps.

von ps

30. Mai 2021

I'm really thankful to the professors for sharing there knowledge and experience and creating this excellent course. I have learnt a a lot. Thank You !!!

von Abanoub Y

28. Dez. 2020

A great course in the very spirit of the original Andrew Ng's ML course with lots of details and explanations of fundamental approaches and techniques.

von Ivan V S

26. Sep. 2021

I​ grade 5 stars, but take in account, that this course is very specific. It provides real basics of NN and NLP and it is more fundamental than apply.

von Baurjan S

29. Aug. 2020

Totally enjoyed it. I took a Deep Learning course a couple of years ago and in some respect, it was a great refreshment form two years ago. Thank you!

von Aanand

3. Feb. 2021

Course well structured. SBOW very well explained and registered firmly. Word embeddings explained very well. Overall very happy from the learning’s

von Long H T

14. Juni 2021

This course is amazing! I could not know that I can learn so many interesting things! I am so happy to take the next course in the specialization.

von Alex M

7. Jan. 2021

Es extenso, pero super interesante la forma de aprender por coursera, cbow model es super chevere. aprendí también, temas de toquenizar textos.

von Ankur G

26. Sep. 2020

More fun if it would have more ungraded coding problem to solve ,It would be optional so that who wants to do more practice can be benefitted.

von Hieu D T

21. Apr. 2021

Very well built lectures. The content is foundational enough for new student like me. I feel more comfortable with keywords in this field now.

von Russell H

18. Aug. 2020

A bit light on the math vs. some other ML courses I have taken, but the good news is that this lets the focus be on the NLP-specific material.

von Kartik S

6. Sep. 2020

The course content was really engaging. This really helped in understanding many of the basic foundational models for pivotal tasks of NLP.

von Prakhar M

10. Nov. 2020

Very intresting and effective way of studing NLP . Totally amazing and 10/10 for the clearity of lecture delivery and video presentation .

von Andrés F R P

16. Nov. 2021

Excelente! Me gustó mucho como enseñan la intuición y matemática detrás de los modelos de lenguaje probabilisticos y Word Embeddings.

von Anshul B

7. März 2021

I liked this better than the 1st course in the specialization. Instructors cover some real fundamental concepts and techniques in NLP

von Vedika P

19. Okt. 2020

Brilliant course. Very enriching content and so very well explained. Challenging assignments made me explore each concept in-depth.


10. Sep. 2020

Excellent course, although the last assignment is very straight-forward and may be good to have a more in depth coding of the loss.