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Opiniones y comentarios de aprendices correspondientes a Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning por parte de deeplearning.ai

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3,228 reseña

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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 course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. 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....

Principales reseñas

AS
8 de mar. de 2019

Good intro course, but google colab assignments need to be improved. And submitting a jupyter notebook was much more easier, why would I want to login to my google account to be a part of this course?

RD
13 de ago. de 2019

Great course to get started with building Convolutional Neural Networks in Keras for building Image Classifiers. This is probably the best way to get beginners into Deep Learning for Computer Vision.

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2601 - 2625 de 3,216 revisiones para Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

por Kaushal D

2 de ago. de 2019

This is fantastic stuff, made simple if you have done earlier course of Deep Learning from Dr. Ng this is at another level, I feel little confident that I may be able to code without copy pasting.. hopefully the next course in the series gets introduced serious stuff..

por Ganesh M S

6 de jul. de 2019

Good course which gives the brief explination on how to use the TensorFlow framework to solve many computer vision problems. This course is designed to such that the beginner too will feel more confident understanding the details of the machine learning techniques.

por Pog P

19 de may. de 2020

Overall, pretty good, clear information. The submissions were a bit annoying because of bugs with the system, but that wasn't anything to do with the course content.

Some of the "graded" exercises could have been a bit more thought-provoking and less "copy & paste".

por Ruchit N

1 de mar. de 2020

This course actually gives you hands-on coding deep neural networks starting from very basic ANN to image classifier. The explanation is easy to understand and is more focused over practical part which is very important. Overall the course is an excellent starter.

por NADER A

15 de ago. de 2019

Hello ,

This was very helpful , I gained some new information.

I can not believe that I finally used the famous tensorflow library , and this is my first time to do picture classification.

This course leaved me with some questions that I will try to research.

por Gothireddy y k

30 de abr. de 2020

Thanks for the course! This course pretty much starts from where I left off i.e. Machine learning course from Andrew NG. And, I am happy using TensorFlow which saves a lot of time to experiment and concentrate on the problem at stake than the program itself!

por Gerardo S

30 de ago. de 2020

I like courses that are longer and more in depth such as the first specialization of deeplearning.ai, I just could not continue that one because financial help always got me financed the first course which I had completed and cannot pay for the other ones

por Philippe K

26 de mar. de 2020

Nice introduction. Tests are too easy. Exercices are easy too, but still is fine, rather I prefer them to be more challenging (like: 'try to play with number of epochs and other parameter to achieve 99% accuracy for example ' and do not guide to much).

por Surya K

5 de abr. de 2020

This course was a little too basic and introductory, personally. But the course structure really makes up for it. It is better suited for someone who is new into this field. Since I had half a year's experience in PyTorch, this course felt too simple.

por Niranjan M D

8 de mar. de 2020

I loved the fact that it was more hands-on than theoretical. Although I did expect some more explanations on some parts.. but the suggested links were good enough for those parts.. Overall, I loved it. Lawrence is really good at what he's doing.

por Shridhar A H

9 de sep. de 2020

Should have provided more explanation about the assignments. The explanation videos about the topics are no longer than 4 minutes. You should know some of the DNN concepts, then you can understands the assignments in depth and more clearly.

por Jay M

24 de ago. de 2019

Not being able to run the notebooks on Coursera was frustrating. Fortunately, running them on colab wasn't difficult - just an unnecessary impediment.

Was nice to see some of the more abstract deep learning terms be put to use fairly easily.

por Yueqi W

11 de ago. de 2019

May be provide resources to learn some senior grammar knowledge for python, because basic knowledge for python does guarantee we could understand the code perfectly, but simply remember its form in case of a particular complex line of code.

por Muhammad H

1 de may. de 2020

I had a background of Andrew Ng's Machine Learning Course so i did not really have any difficulties with it. However, a bit more detail on conv nets' theory will make this course much better. Still, I loved this. Thank you deeplearning.ai!

por Stephen B

11 de abr. de 2019

Good course, somewhat easy, but I anticipate a lot more new and interesting and useful stuff in the remaining sessions yet to be offered. It would be good to point out what is now Tensorflow 2.0. I anxiously await the new material. Thanks!

por Rami K

29 de may. de 2019

Great course, excellent contents. I would have loved more smooth intro about the generator as I found we suddenly went to talking about this generator without prior introduction. To be honest, I still cant see the value of this generator!

por Davide C

12 de jul. de 2020

Good introduction to TensorFlow, but that is all there is.

Don't expect to gain any understanding in how neural networks are and work from here. It is only about learning the TF API.

I think the title is a little misleading in that sense.

por Lucrezia

26 de mar. de 2020

Very conceptual course, with few exercises to help you learning how to build a basic convoluted neural network to a dataset of images. I enjoyed it, also because it provides many sources to use if you want to dive deeper on your own.

por Wenjing L

3 de may. de 2019

I learnt PyTorch prior to TensorFlow. Still found this course is very helpful. Thanks to the instructors. The only thing is, I wish all the reading links could be listed down on one page, and all the notebook links arranged together.

por Mohamed S R I

21 de sep. de 2019

Laurence is an expert in this field. The material covered in this course is relatively basic, but I think it is a good introductory course for TensorFlow. I was expecting more / elaborate material for the graded assignments, though.

por Mohammed F

26 de abr. de 2019

I took this course for the more low-level API in TensorFlow since I already had experience with Keras. But it was still a fun course to watch and an excellent start for people who are just beginning their journey in Deep Learning.

por 雾雨千秋

26 de ago. de 2019

The week four programming exercise needs some improvements. I can not unzip the data, so I had to download this exercise and finished it in local environment. Finally, I hope some videos can have Chinese subtitle in the future.

por 杨亲

11 de oct. de 2020

This one is basically an intro on how to use tensor flow apis to build neural networks. it is very useful to learn how to use these APIs and some Python code. I'm looking forward to learn more about CNNs in the next course.

por Brian ( B

16 de oct. de 2019

very practical courses with examples. May address some knowledge on NN architecture design, such as why place an additional flatten layer before the final layer. Some cases, we didn't need such layer and the reason why?

por Ashvith S

12 de mar. de 2021

Probably one of the best course!! I think the team needs to fix some parts, where the instructions aren't clear. Honestly, it is amazing that we can create a simple machine learning model with just a few lines of code!!