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Natural Language Processing in TensorFlow に戻る による Natural Language Processing in TensorFlow の受講者のレビューおよびフィードバック



If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 3 of the TensorFlow Specialization, you will build natural language processing systems using TensorFlow. You will learn to process text, including tokenizing and representing sentences as vectors, so that they can be input to a neural network. You’ll also learn to apply RNNs, GRUs, and LSTMs in TensorFlow. Finally, you’ll get to train an LSTM on existing text to create original poetry! The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....




Excellent. Isn't Laurence just great! Fantastically deep knowledge, easy learning style, very practical presentation. And funny! A pure joy, highly relevant and extremely useful of course. Thank you!



Great course for anyone interested in NLP! This course focuses on practical learning instead of overburdening students with theory. Would recommend this to every NLP beginner/enthusiast out there!!


Natural Language Processing in TensorFlow: 601 - 625 / 934 レビュー

by Parvez M


A fantastic way of explaining things. Used a number of datasets to introduced different situations. However, it contains some drawbacks. For example, maybe the notebook is written using old API, hence the data are needed to be wrapped using `np.array()`. Again, It would be better if the notebooks are graded too.

by Ashutosh S


This course should included other Neural methods for NLP to practice in tensorflow and the excercises should be a bit more difficult, they were way too easy to deal with. Assignments help a lot in getting hands on experience. The course overall, gave a nice and concise overview of the tensorflow framework.

by Pranjal J


The course provides elementary guidance to get start with NLP. The gist of pre-processing concepts are nicely explained. However, it lacks the weekly graded assignments. Overall, a great course to begin with your NLP application but lacks thorough mathematical concepts that are used under the hood!

by Michael M


Enjoyed the course, more content that the other lessons in the series. Still lacks notes and direct codes to save and practice on our own rather using the google colab that could be in the future require subscription. Good explanations can't wait to start the last course on the series.

by Wouter t B


Unfortunately the exercises in this course are all ungraded, they don't really have a benchmark goal (in contrast to the earlier courses in the specialization). You're still able to work with 'ungraded' assignments but the difficulty level seems a bit lower.

by Benjamin T


More intuition for different choices of hyperparameters (layer types, layer specifications) would have been great.

Named Entity Recognition is one of the most important NLP tasks in the Industry, but it is completely missing.

Transformers are missing.

by Vishal N


I'm not as satisfied with this course as I am with CNN or Intro to TensorFlow, main reason being there was no graded exercise materials unlike the other two above mentioned ones. I still loved the videos nonetheless. Thanks Laurence and Andrew :)

by Shaurya K P


I'm missing the programming assignments as in earlier courses also i also felt a lack in links of google notebook and we only have videos of the programs working rather than getting hands on with links to corresponding google colab notebooks.

by Ali A


More info might be provided especially on creating model architecture. I mean in hyperparameter tuning side should be more clarified. What happened when we change emdedding dimension is important to understand whole logic as an example.

by Balaji K


Extremely interesting field and am super excited to experience the Tensorflow libraries where so much (of code, which I used to write in raw python, years ago !) is encapsulated in simple, ready-to-consume, yet powerful modules.

by René S


Worldclass teachers. But I am a bit sad, that the programming challenges are just optional. In the previouse courses the coding exercises have been mandatory, which helped me to be more motivated to do them and test my skills.

by Yi S


At first I though the courses paid too much attention on data preprocessing when implementing NLP.

Well, how to figure out the right way to deal with natural language is what we should learn in this course and it really helps!

by Parth S


This complete course provides you with a great welcome journey in the world of NLP. Laurence really provided the basics required to understand the topics. Additionally, it was fun to listen to a talk of Andrew & Lawrence.

by Abhinav T


The course was overall awesome as is Laurence. But google colab repositories were first of all ungraded Idk why & there weren't any well defined instructions on at least what do we need to do on the next code snippet.

by 家彬 朱


A good course for NLP, but I like the previous courses more. This course does not deliver the teachings as clear as the previous courses. And I can feel that we've skipped a lot of things in this course.

by Damon W


These classes are excelling practical examples of how to use tensorflow for various problem types. My only objection is they are slightly light on the actual, behind the scenes, math and intuition.

by Michele M C


This course represents a step forward to the previous courses on CNN and ANN. Very interesting themse and functionalities learnt in this one. Please fix third homework code because zip file is 404.

by Miguel R


The course is great, but the assignments were not designed as well as the ones in the previous courses. I believe that a careful design of the assignments could significant improve the experience.

by Arjun S


Was really easy as compared to CNNs. I wish this had more notebook evaluations like the course for CNNs since that really made me feel good overcoming all the tasks, especially the last one.

by Dimitry I


Good course that gives you basic understanding of word embeddings, sequence analysis, and many other things. Thank you for Mr. Moroney and the entire Coursera team for making it available.

by Enyang W


NLP is a very interesting topic, and this course brings me closer to actually working on a NLP project myself. I don't know why exactly, but I cannot be fully satisfied with this course.



The Course was really great I enjoyed learning, just a little suggestion Laurence, your voice was too low while going through the code in the collab, but still I enjoyed learning a lot

by Aparna M


Good course. Especially the sequence models part was covered really well. I enjoyed watching all the videos and the reading materials, notebooks were well explanative. Thank you.

by Dr.G.N.K.Sureshbabu


A good course which gave a in depth overview of NLP classes in tensorflow . Need to include more challenging assignments and also should bring in modules on BERT which is SOTA.

by William M


Excellent course but I would have liked to have exercises that required coding. I learn better by writing code, figuring out the order, etc. Still, a very good course.