Very Very disappointed. "Shallow" is the word comes into my mind when I think about the lectures of this course. Materials are top-notch, but not enough attention were given into the details. Felt like it was made in a hurry. Why would someone pay a good amount of bucks to take a course like this that can be finished within a single day ?

Programming exercises are badly described, very often it is not obvious what then expect from you. Also some of them are broken, are correct answer is wrong and you are expected to reproduce the wrong answer (week 1).

Giving feed back so it may trigger some evaluation on this course. The course is very weak. Lacks material and engagement feeling. I would say increase the aterial 800-1000 percent , add homeworks, etc..

This seems like a beginner's class than an intermediate class. Can't you make some interesting coding assignments rather than the colab ones to run. Really boring this course

Not suited for beginners, no details were covered. This course is for people who have experience working with Tensorflow and just want to brush-up their skills.

Really a very beginner course. I am not sure they mentioned it or not. But they should ideally put it in the course description very clearly

It was not so great as I thought. The exercises and quizes were not challenging enough. It does not make you an NLP expert.

Very few details of LSTM are covered, do not think it is enough.

weak examples. no programming exercise.

Poorly designed and graded exercises.

Nothing to say besides disappointing!

do not take this course

It needs more homework.

This course is very good for some applications. I am interested in using natural language programming to do a translating program Spanish to English and viceversa thru recognizing tokenizer sequences that map onto translated tokenizer sequences via a lookup table.

It does confirm whether TensorFlow or Keras are the tools to do so.

My doubt is where does one to find out exactly what I want?

Plus, it does not state where or which is next course.

At any rate, I a very grateful for the information run thru, to know which way they are going, that does not interest me at all.

One of the best places to start learning applied NLP in tensorflow. I tried books on ML for concepts but this really got me flowing with coding the ml programs for NLP. The delivery style was lovely. I love the style of instructor (Laurence). I haven't done the deep learning specialisation but the method with which the material was discussed made it easy to grasp the concept behind NLP while implementing it in code at the same time. Must do for all beginners in deep learning and NLP.

This course is perfect for beginners to have a grasp of the concept of utilizing tensorflow - keras tools and function to process natural language and create models for learning it. It has some deep explanations for why the models behave this way but not other ways. There are also some really useful tips that are worth to take note and can help AI researchers to save some times trying to figure out how to configure the environment, model structures etc.

Pros:

Laurence is an excellent tutor. He makes the whole experience very natural and although it is not a full introduction to deep learning, he gives an intuition behind all the steps, layers, approaches and functions. Highly recommended to someone starting out in NLP with TensorFlow.

Cons:

Exercises are only quizzes which are extremely easy. I miss graded notebooks but I understand that there may have been some computational constraints.

My first courses in AI was in Tensorflow and from that day i fell in love with AI. But i don't understanded some many thing about Deep Learning and i stoped this specialization and i learned about teorical Deep Learning with books and Andrew DL specialization.

So, i mean that i'm practice and develop AI application because of you. And i reaally appreciate your teachings. I find out my vocation with this specialization.

There are lot of courses available related to processing image data, but very few on NLP. The course was really good and helped me a lot. It would be helpful if a course is designed specifically keeping in mind the NLP data and the tasks associated with processing text data. If you could please make a video/post/blog on how to perform named entity recognition using sequence models with neural networks.

The content was quite good. I felt contented after watching all the videos in the course as I wanted some hands on experience in TensorFlow. Just a small suggestion to increase the volume of the videos. I faced a tough time watching videos on the Coursera app in my mobile. Coming to content wise, an excellent course to begin your path in NLP. Looking forward for the last course in the specialization.

Another outstanding course by Laurence Moroney. I like the clear and concise way that Laurence teached the complex subjects and his step-by-step approach to building up the models without getting bogged down with too much jargon or theory (and math!) behind the models. The courses (& exercises) are helping me apply the concepts to very practical problems. I enjoyed this course - Thanks Laurence!

Nice explanation by Mr. Lawrence about the prowess of Tensorflow module and how we use it to make a big impact in our Machine Learning problems using many datasets, such as ImageData Generator, Natural Language Processing, etc. Thank you also to Mr. Andrew and DeepLearnig.AI to support this kind of open-source library for people to also contributed to advancing the world of Machine Learning

Nice experience taking this course.Precise and to the point introduction of topics and a really nice way to start programming the models without going much into theory. Covers good ground in NLP using Deep Learning.Just got a feeling that the explanation of RNN and LSTM can be bit more elaborated so as to make them understand little better but all an all a vergy good course.

This course is a great introduction to NLP processing with Tensorflow. It emphasize that more effort is required in terms of data pre-processing as well as the different variations to implement RNN (LSTM,GRU,Conv1D). The last part with text generation is very interesting as well to understand how to extrapolate text generation from an initial classification problem.

I enjoyed this course a lot. The concepts are not easy but Laurence the instructor does a really good job at breaking them down with practical examples and concrete implementation of the models with Tensor Flow. I went from knowing nothing in NLP to using cutting edge tools to implement those algorithms. Millions of thanks to our teachers Laurence and Dr Andrew Y.