Natural Language Processing in TensorFlow
DeepLearning.AI TensorFlow Developer,
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 deeplearning.ai 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 deeplearning.ai 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.
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| Rating | 4.3★ based on 250 ratings |
|---|---|
| Length | 6 weeks |
| Effort | 4 weeks of study, 4-5 hours/week |
| Starts | Jun 28 (44 weeks ago) |
| Cost | $49 |
| From | deeplearning.ai via Coursera |
| Instructor | Laurence Moroney |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Software Development Machine Learning |
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What people are saying
natural language processing
This is good course for those who are want to practice in natural language processing in Tensor Flow and also learned sentiment analysis it is having wonderful stuff for beginners very useful and fun Thank you to the team for putting this together!
very interesting and well presented course Since the course doesn't mention "Introduction" to NLP, I thought that the course will provide a detail insights to Natural Language Processing but the course only covers basics of it.
Taught a lot about natural language processing.
It is very helpful course for beginners in NLP subject Great and clear instructions on how to get started with natural language processing in what in Tensorflow Keras.
An excellent course by Laurence Moroney on performing Natural Language Processing with concise content and clear explanation.
This last one, natural language processing, can be completed in an afternoon, all four weeks.
It is a very easy to follow and interesting course to start with Natural Language Processing in TensorFlow.
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deep learning
This course is a far cry from Andrew Ng's deep learning specialization and refers to Sequence Models from that specialization at the drop of a hat.
In short, no use doing this one, unless you have done sequence models (course 5) of deep learning specialization.
The course is really nice, especially if you just start working with TensorFlow.But I think it could be better to have 1 week for all course, with 8-10 min videos, instead of splitting it into 4 Weeks with 1-2 min videos GJ This is a great course but I will advise taking Andrew's "Deep Learning Specialization" before this.
A very good course to start with basic NLP using deep learning.
An adequate course that helped me understand more about NLP in tensorflow, in addition to the content provided in the deep learning specialization course Thank you so much for such a clear explanation and interesting course.
Probably more valuable after completing Deep Learning Specialization/Sequence Models by Andrew Ng (https://www.coursera.org/learn/nlp-sequence-models) Excelente!
Excellent course to take after completing Deep Learning Specialization As previous Courses of this Specialization, this Course is very suited to teach you the main concepts quickly.
A bit more evaluation steps, as per in Andrew's Deep Learning Specialisation, would require more commitment from students.
I was able to very quickly get a grasp of how to approach text data and gained both an understanding of how to represent language-based data as well as how to apply deep learning to do some pretty amazing things.
Deep Learning with Python textbook by Francois Chollet, the github repo for which is public and the notebooks are almost exactly the same as here but more in-depth).
Although it feels like a slightly watered-down version of Andrew Ng's 5 course deep learning specialization.
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for beginners
Thank you Excellent Explanation by Laurence for beginners ; easy understanding of concepts Very good course for beginners including good exercises.
Missed graded assigments Extremely useful good very helpful in understanding the basics excellent course for beginners in NLP Detailed Description is still missing, makes you sometime to google and find the exact understanding.
Nice and clear They are course is well oriented for beginners.
learned a lot :) Good course, very helpful for beginners Good lightweight course with clear content and timelines to complete the course.
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laurence moroney
I found it great for the following reasons:- Laurence Moroney (Instructor) was very professional and clear while delivering the knowledge- The introductions by Andrew NG were really nice- Easy to understand codes and understanding of thr underlying principles- Varied topics such as CNN, NLP & Time Series- Very insightful by providing expert opinions about different ways of model optimizationI really enjoyed the course and I thank the instructor for the same :) Awesome Course!!
I really loved the way Laurence Moroney step by step explained every concept.
Brilliantly explained and very good part was the code explanation in Notebook My Heartfelt thanks to Laurence Moroney sir and Andrew ng for presenting this great lecture.
Amazing course by Laurence Moroney.
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word embeddings
Teaches NLP thoroughly, going from the basics such as tokenization and padding to complex topics such as word embeddings and sequence models (like RNNs, LSTMs) s 5 Stars for practical knowledge on sequence based models A very basic intro to NLP, met the objectives stated earlier.
Teaches NLP thoroughly, going from the basics such as tokenization and padding to complex topics such as word embeddings and sequence models (like RNNs, LSTMs and GRUs).
Thank you Very Much :) It would be better to have acess to the notebook of lessons and some explainations Helped me with my understanding of word embeddings and helped me improve my skillset in NLP Please transfer the exercises from CoLab to Coursera.
Good course that gives you basic understanding of word embeddings, sequence analysis, and many other things.
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machine learning
Excellent courseGave me a brief idea with practical experience about how to process strings for machine learning.
Practical skills for practical machine learning!
great start for a machine learning student Laurence explains the code really clearly!
After the great expectations built from taking Andrew's deeplearning specialization and machine learning course, I must say the first three courses of this specialization have been extremely disappointing.
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| Rating | 4.3★ based on 250 ratings |
|---|---|
| Length | 6 weeks |
| Effort | 4 weeks of study, 4-5 hours/week |
| Starts | Jun 28 (44 weeks ago) |
| Cost | $49 |
| From | deeplearning.ai via Coursera |
| Instructor | Laurence Moroney |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Software Development Machine Learning |
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