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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

4.7
4,710 calificaciones
932 revisiones

Acerca del Curso

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 revisiones

AS

Mar 09, 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

Aug 14, 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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776 - 800 de 933 revisiones para Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

por Jingwei L

Aug 22, 2019

A brilliant start for a learner who is eager to engage in AI. For me, a Chinese practitioner, the Chinese subtitle could be uploaded as soon as possible.

por Jay M

Aug 24, 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 Manikantam C

Aug 26, 2019

I think there can be more reference videos so that we can understand in depth about how convolution works! but these videos do help maximum to understand concepts.

por Tongxi L

Jul 02, 2019

good introduction, but only introduction is not practice, just classifier from tensorflow dataset is not helpful for real problem

por Juan I Z M

Jul 03, 2019

this is a great intro course but requires the student to be somewhat proficient in ML and DL concepts

por Egor M

Jul 07, 2019

I guess, it could be much more than only 4 weeks

por Ganesh M S

Jul 06, 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 Antariksh P

Jul 10, 2019

Great course but should go in-depth about the functions used. Also, the part about making a custom classifier for multiple categories (more than two categories was missing)!

por Juan F P

Jul 14, 2019

The course was great, and it was a wonderful introduction to Tensorflow, I would like to go beyond the basic, having more technical material that cover the topic more deeply.

por Hamad

Jul 15, 2019

Good introductory course.

por Kristopher J

Sep 01, 2019

The course has a lot of good material, and is a great follow-up to the more theoretical Deep Learning Specialization.

However, I can't give it five stars because the exercises are a bit repetitive, and the quizzes have some very poorly worded questions. I know this is a new course, so I hope they can smooth out some of these rough edges.

por gu t

Aug 30, 2019

too easy for experienced programmer, only introduce keras instead of full tensorflow api, it will helps if an advanced course can be offered.

por zhou s

Sep 01, 2019

Elementary introduction to Tensorflow

por Mr. J

Sep 06, 2019

significant advancement from previous courses

a practicum

por Daniel P G

Sep 05, 2019

Very beginner friendly. Evaluation task could be a little more challenging than just copy-pasting the example code.

por Avinash M

Sep 06, 2019

I thoroughly enjoyed the course and programming various CNNs on TensorFlow. However, in certain lectures (especially the ones with the horse/human data sets), the instructor could spend some more time explaining the process of downloading and storing the training and validation images. It took me some effort and quite a lot of Googling to figure out those parts of the code. While that might not be directly related to the task at hand (binary classification) it is, in my opinion, necessary to understand some of these ancillary tasks as well. Perhaps these explanations could be included as optional videos for those who wish to understand these features of TF.

por Michalis F

Sep 06, 2019

too introductory, can be done in a couple of hours, very good instructor

por Nikolay R

Sep 11, 2019

Very, very basic course for absolute beginners. It makes sure you know enough to build and train models for simple image recognition tasks. 4 weeks is a crazy long period for it, though. I finished it in 2.5 days (I have previous exposure though), but even a beginner should be able to do it in 1 week.

por Richard H

Sep 13, 2019

Great introduction to using Tensorflow to implement convolutional networks.

I took the Stanford course by Andrew Ng first, so many of the concepts were very familiar - in some cases, the detail was just a little bit shallow - probably to avoid interfering with getting on with implementation - but this course certainly had references outside the course to some more detailed information on topics like how convolutions help identify features or the learning factor.

The jupiter notebooks were great in that you don't need to worry about the environment much - it's already set up - a big worry for me for many of these types of courses. But there were quirks, and a few times I (and some of the other students) could get tripped up for a little while. If you are a developer like I used to be, then troubleshooting and debugging environment/code issues is a small hurdle though.

Kudos to the instructors and those that set up the course - this is otherwise very hard material to teach and set up good "hands on" evaluation, which they did really well, a couple kinks aside.

por Xinhui H

Sep 15, 2019

Good introductory course. With a lot of focus on codes. Lack of theoretical stuff though.

por João A J d S

Apr 30, 2019

It's a great course! Very well structured, with an amazing amount of jupyter Notebooks (Colab) to work with, in a real hands on approach.

Just one criticism, which is why I didn't classify it as 5 Star: There isn't much of an evaluation. The tests are a bit easy, and it would be good to have at least one extensive assignment (maybe with other datasets...).

It's just that I feel the contents were really good. But if I can just pass the tests easily, I feel it doesn't really count as much of a "quality stamp" (to have passed this course).

por Abhijeet M

May 26, 2019

helpful insights about convolution and pooling. I could see how they work together.

por Abhijit V

Sep 20, 2019

Got some basic idea of deep learning and tensorflow

por Mohamed S R I

Sep 22, 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 Manuel A

Sep 21, 2019

Basic tensorflow code and simple examples, its ok to getting started