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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
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12,703 calificaciones
2,689 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

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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76 - 100 de 2,687 revisiones para Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

por Hakesh k

Jan 05, 2020

Amazing way of putting all the stuff together

por Muthiah A

Jan 06, 2020

Useful start for practitioner.

por Rushikesh W

Jan 04, 2020

Good practice for coding on tf

por Henrik R

Jan 21, 2020

The course is ok-ish, as are all the other courses in the specialization. This review is for all the courses in the specialization. I have a general shallow overview of DL but wanted to learn about TensorFlow and about Keras. For this it provides a good overview. You could learn it from tutorials too but at least I benefit from taking a course, as it motivates me to finish. But, the material is very shallow and it is a shame that there are close to no graded exercises. The quizzes are super easy. And there is no capstone project. If I didn't know the basics before I probably wouldn't have understood anything. If you know a bit of DL beforehand you can easily take one course per day. The fact that earning the certificates unfortunately degrades the value of it. If you finish in a month (and therefore only pay for a month) I think it is worth the price, even if what you learn is not that deep.

por thomas y

Oct 10, 2019

I get that this is a separate course from Ng's deep learning course, but I found the lack of theory (or even recommendations of best practices) disturbing. Additionally, I thought the videos were way too short and would have appreciated it if they had gone into detail into each Keras method used, the parameters for it, etc. For example, on the last assignment we were supposed to use a callback on accuracy to end training, but nowhere in the videos did it mention how fit_generator() handles callbacks as opposed to how they were handled with fit().

Lastly, and most importantly, this course was advertised to be a course on Tensorflow. However, this is not the case. This is a course on Keras; Tensorflow's API. If you came here looking for how to implement a DL algorithm from scratch in TF, this is not the course for you (or me apparently).

por Ivan N

May 19, 2019

I think this is a great way to introduce NN to people that have never seen one.

But there was very little depth in this course. I finished the 4 weeks in an afternoon. The external references were at times way too advanced, while the exercise code was way too simple. That being said, the Jupyter notebooks were a great material and helped me start with NN really quickly. The MNIST dataset is brilliant and hank you for showing how to do it.

The reason why I gave 3 stars is because the MOOCs aI have done in the past were much more extensive and gave plenty of theoretical background. Some people might think that the lack of theory lowers the entry bar for students, but in my book that's a tutorial not a course.

Save yourself the $40 price tag and buy a book on the topic, there are plenty out there.

por Alon L

Mar 19, 2019

Material is very well explained and very relevant but the course is short in comparison to other deeplearning.ai courses before and could be richer both in content and in exercises (which are also not graded)

por Philip D

Apr 06, 2019

Decent enough but much too abbreviated and lacking the depth I expected from a deeplearning.ai course after taking their deep learning specialization.

por Stavros K G

Mar 10, 2019

I know that it is an introduction but I would like more staff .

por Antonio S

Sep 17, 2019

I am quite disappointed with this course. First, it should not been called "Introduction to TensorFlow" but "Introduction to Keras", which is a TensorFlows' (TF) API that entails a higher layer of abstraction. Basic data structures, estimators, graphs, etc. are not explained through the course. Second, video lessons are too superficial and lack of content. They remind me to those of the Machine Learning Crash Course from Google. That is, as an opener/introduction for Deep Learning (DL) are fine but they are far from being an essential training tool in DL (unlike the Deep Learning Specialization here in Coursera). Finally, content is too basic. This course requires an intermediate level, so students are supposed to be already familiar with basic DL concepts. I understand that this first course within the specialization is an introduction, but I just begun the next course (Convolutional Neural Networks in TF) and it is more of the same. Laurence is still working on the binary classification problem and only at the end he treats the multi-class problem. Instead, I was expecting to implement CNN models like ResNets, Inception networks, and applications like object detection or face recognition in TF (not in Keras). For me, it is not worth spending time and money for what you learn in this course. The good part is that, because videos are short and exercise are easy, you can finish the whole course in just one week (or less if you are 100% working on it).

por Dragos B

Mar 15, 2020

Maybe I had unrealistic expectations following the original 5 courses from deeplearning.ai. I understand the target audience and need for simplification, BUT there are multiple outright wrong statements, that are unacceptable (will list below):

1 `Softmax takes a set of values, and effectively picks the biggest one, so, for example, if the output of the last layer looks like [0.1, 0.1, 0.05, 0.1, 9.5, 0.1, 0.05, 0.05, 0.05], it saves you from fishing through it looking for the biggest value, and turns it into [0,0,0,0,1,0,0,0,0] -- The goal is to save a lot of coding!` - no it doesn't do that, it takes n numbers and gives n numbers which sum to one and respect all original inequalities. and no it doesn't save time, you still need an argmax.

2 in the first course there's a linear regression trying to learn f(x)=2x-1. The course says you can't get it exactly because you don't have enough data. Of course you have enough data, 2 points are enough to describe a line, and that regression has a closed form solution. SGD with fixed LR is the only problem.

3. Immediately after, also first lesson, it says that sometimes loss goes up and that's called overfitting.

Those were just a few...really I understand it doing baby steps for developers without maths background, but I'm not sure this is doing them any favors..I've also showed these to a bunch of my colleagues and we were on the same page about it

por Aladdin P

Aug 04, 2020

I am not very satisfied with the course. It does feel quite professionally made, but there is no depth. It feels as if the teachers of the course had some difficulty when deciding on the prerequisites. I think it would have been clearer if the course would just have said: take this course after the deep learning specialization because this will build on knowledge from previous courses. Then, focus ONLY on teaching the coding part, explain what is TF, what is Keras, in DEPTH. For example, all the quizzes are more theorethical questions: these should be ALL code in TensorFlow. E.g, what is the following code doing? I guess it's just the first course, so depth is not expected but what I've read so far, it wont change in the following courses. I'm dissapointed and Andrew you should set a higher standard for your courses. Hope you will take lessons and not let this happen in future courses, I wasted my money and time on this.

por abdallahDrwesh

Jun 20, 2020

No deep details for functions used

por Walter H L P

Aug 06, 2019

Code and exercises look like they were made in a hurry, with a lot of errors that have not been addressed yet, even after been reported about 3 months ago. No challenging practical exercise (just need to copy the code from the previous notebook that the instructor supplied) (maybe making the function print "Reached X% accuracy so cancelling training!" was necessary to fool the grader). Weak theoretical test. I had high expectations, and now I am disappointed with this deeplearning.ai course. I do not recommend, TensorFlow guide have better material to learn about it.

por Mahdi S

Nov 09, 2019

I don't actually get the purpose of this course: teaching deep learning or teaching deep learning with TF? Can there be anything else? If the former is the aim, one needs to learn how a deep learning algorithm works and why it is successful. If the goal is teaching TF for people who are familiar with deep learning, first the structure and logic behind TF and then the coding parts should be taught line by line with details.

This course, in my point of vies, has nothing to present.

por Siddhanth D

Oct 13, 2019

What a crap professor. Really wish Andrew Ng taught this course instead. I have no clue what this teacher is talking about he makes 2-3 min videos of complicated material and blabbers about it while referring us to online videos and other resources instead of just explaining it.

por Mohammadreza M

Oct 19, 2020

The course is very superficial and rarely add something to your knowledge. Assignments are simple and do not teach you how to use TF in your projects.

por Stephen F

Jun 07, 2019

I mistakenly bought this course , Note 43 euro is for this one simple module, be aware please!!

por Ahmad F

May 06, 2020

If you're starting out as a beginner AI practitioner, this is a very good introductory course. The prerequisites for going through the classes are really low. You just have to know basic python and the basic mechanics of deep neural networks beforehand. After completing this course, you'll be very proficient at modelling neural networks to classify images with very high accuracy using tensorflow keras.

This course also explains briefly how to import data of your choice to your neural network to train on, which I think is very cool. It also teaches you about convolutional neural networks, which is what the top industry experts use to do their AI jobs. The exercises in this course are well made, they help you really understand the concepts by making you code them by yourself. All in all, this is a very good introductory course, and Andy Morone is an amazing teacher.

por Frank Z

Jul 15, 2020

This course is very friendly to beginners starting to get to know TensorFlow. The only skill needed is basic Python programming. Another good point for this course is students don't have to obtain a local machine that could run the TensorFlow. The tasks could be done over Google Co-lab, which is very conveniently friendly. The only shortcut for this course would be the source codes provided are based on TensorFlow 1.X. Right now, the TensorFlow has released 2.X. Since tf V2 has taken out some functions in V1 as well as changes some expression, it would be very inconvenient if you wanna download the code and test or do your work on your local machine.

Overall, this is a course that I would highly recommend as a beginner.

por Edgar C O

Jun 23, 2020

As an introductory course to the Tensorflow platform I think it is excellent. As it is mentioned in the title this is not a course where you are going to see in depth what it is behind the algorithms or the theory behind the implementation but it provides extra links to other sources where the interested student can read on their own, which I think is good. It is self-contained, the material in the course it is well explained and the ideas about how to use the platform and the ideas of how to solve the problems are well-defined. The exercises are defined in such way that the student can immediately used what he/she learned from previous materials. It is a great introduction to Tensorflow.

por Alan F T

Sep 28, 2020

This is an excellent foundational course on a complex topic. I especially like the application of the course examples in real-world deployment type assignments. The use of colab is very nice, it is not a technology that I have used before however its 'jupyter' like interface is very comfortable and I like how it is deployed and accessible on virtual machines all the time. The only criticism I have is that the assignment grading is a little rigid and there is not a lot of valuable feedback if fails (i.e. it could be badly coded or it could be something as trivial as using the wrong number of nodes in a layer! - this could be explained better I feel)

por Jeremy V K

Jun 24, 2020

Amazing class! As an absolute beginner, I wanted to learn machine learning and AI but didn't even known where to start. I even started a different machine learning course which I could not follow well, and expected similar results with this class. But this class, this class is aimed at beginners, no need for any pre-requisite knowledge and the google colab environment ensures that it doesn't matter what hardware you currently have, since its all done in the cloud. Also the practice notebooks are very detailed about each sections of the program. I'm not a master at machine learning, but atleast after this course I feel that I too can learn it.

por Dhamotharan B

Jun 29, 2020

I have used Tensorflow in my projects but never know some of the tricks which could improve the model.I was very dependent on transfer learning. But, now after getting to know much about Tensorflow, I feel so confident . A basic understanding of how model works with Tensorflow is essential and Laurence Monorey provides you some of those basic tricks and concepts of how neural networks works with Tensorflow. I can assure anyone here taking this course would definitely give a try to adjust the way they have approached towards implementing Tensorflow in their projects. Thanks Andrew and Coursera for bring up this initiative.

por Prashant S

May 21, 2020

I found this course very helpful because of working example at every step. First there is step by step explanation of each line of code after which you can play around with the code by making small modifications to it and observing results. It is not heavy on math behind machine learning but there are certainly lot of new terms. Most of time i googled those term to learn a bit more about those. Overall, instructor explanation is extremely good and easy to follow up. Its extremely important to play around with the code samples. All i needed was a browser and no installation on my laptop to finish this course.