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Avis et commentaires pour d'étudiants pour Named Entity Recognition using LSTMs with Keras par Coursera Project Network

4.4
étoiles
159 évaluations
36 avis

À propos du cours

In this 1-hour long project-based course, you will use the Keras API with TensorFlow as its backend to build and train a bidirectional LSTM neural network model to recognize named entities in text data. Named entity recognition models can be used to identify mentions of people, locations, organizations, etc. Named entity recognition is not only a standalone tool for information extraction, but it also an invaluable preprocessing step for many downstream natural language processing applications like machine translation, question answering, and text summarization. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Keras pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Meilleurs avis

YK
18 juin 2021

End to End example of how to implement NLP NER in Keras using bi directional LSTM. Completed notebook can be found in the Coursera project resource page.

BN
29 mai 2020

Excellent short course with hands on exercise. Wish to do more free courses.

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1 - 25 sur 36 Avis pour Named Entity Recognition using LSTMs with Keras

par Mohamed H G

27 mai 2020

You could increase the time limit for the instructor to explain the functions and logic behind it more elaborately.

And i would be happy if they provided an option for compiling on our own desktops which would be quicker and more efficient on real world Data.

The online GPU was dependent on the internet connectivity and wasn't efficient enough.

On the whole, the course was helpful, Thanks.

par Ashutosh R

28 mai 2020

Explanations of functions and library used were a little less, otherwise a good course

par Raihan R

8 mai 2020

A very short course with very little explanation. Rhyme server keeps restarting without any apparent reason. Probably a YouTube video with a Google Colaboratory workbook would have sufficed. Without exercises to practice on, students can only mindlessly copy what the instructor just did.

par Shashi K G

6 sept. 2020

This project is a short end-end show. Quickest way to know the process.

par Anantha P

25 mai 2020

Good course covering all the basics required to train a NER model using LSTM without requiring a lot of per-requisite knowledge. Guided project made it easy to follow the instructor and to get an hands on experience

par Rajat R B

31 mai 2020

Rhyme never connected and project was too simple. Elaborate explanations would help!

par anurag g

7 juil. 2020

The course content was very elementary for someone who wants to create a working project using NER. Author was directly using all the concepts in the code without any explanation. So, it was just copy-pasting the code. This will help only if you want an elementary piece of code without any explanation. Not worth your money!!

par Yaron K

19 juin 2021

End to End example of how to implement NLP NER in Keras using bi directional LSTM. Completed notebook can be found in the Coursera project resource page.

par Biranchi N N

30 mai 2020

Excellent short course with hands on exercise. Wish to do more free courses.

par Mwenda

3 avr. 2021

Great course! Gives you a solid understanding of NER.

par Patrick O

31 mai 2020

Excellent course on revising LSTMs and Keras!

par Aldrin C V

23 juin 2020

A good way to start learning DL using Keras

par Ramprasath A

20 mai 2020

It served the purpose..

par farhan a j

7 oct. 2020

Great explanation

par serdar b

19 janv. 2021

Good instructor.

par janmejay b

28 sept. 2020

Nice project...

par Sylvert T

15 mai 2020

Help me a lot

par Kamlesh C

18 juin 2020

Thank you...

par Gaikwad N

23 juil. 2020

Excellent

par Rutal M

2 juin 2020

nice one

par Doss D

14 juin 2020

Thank u

par HASSAINAR T S

4 juin 2020

Awesome

par sarithanakkala

23 juin 2020

Useful

par Rifat R

5 juin 2020

Great

par p s

23 juin 2020

Nice