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Avis et commentaires pour l'étudiant pour Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning par

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306 avis

À propos du cours

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 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. The full TensorFlow Specialization will be available later this year, but you can get started with Course 1, Introduction to Tensorflow for AI, ML and DL, available now on Coursera....

Meilleurs avis


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?


Jun 07, 2019

An awesome practical course that helps me to start creating my first neural networks using keras in such great methods, the instructor is very good at delivering the knowledge he has\n\n.

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1 - 25 sur 337 Examens pour Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

par Ben B

Mar 17, 2019

This felt like a glorified tutorial for TensorFlow/Keras. I expected more in-depth treatment of the material. E.g. covering more ground (regularization wasn't mentioned at all), or going into more depth on the machine learning theory (why are we using this activation function, this loss, or this optimiser) or practical tips (e.g. discussions of network design) or the tools we are using (e.g. what exactly is TensorFlow, what is Keras, how do they relate to each other, how do they work under the hood).

I also raised some issues and PRs on the github repo for the worksheets to correct problems in some of the worksheets, but these were not responded to by the time I had finished the course over a week later, despite the low volume of issues and PRs on that repo.

I paid for the course upon getting to the first quiz so that I could have my answers graded, but I don't feel that I got my money's worth.

par Kristina P

Mar 14, 2019

I was expecting a more elaborate content and graded programming exercises for those who pay for the course. Instead the major part of the content is based on the FREE tutorials available on TensorFlow website. Besides, the course is split to 4 weeks but the complexity of the content does not fit to the announced period. It can be easily completed within few days or less by any avearage CV researcher. It is populated with a bunch of very short videos with 'surface scratching' explanations. A targeted learner seems to be an undegrad. Also, some important concepts of TensorFlow were not explained (ex: what is tensor? etc.) Overall, I am disappointed and consider this a waste of money. eventhough, it can be useful as an audit for those who need some structure in self-education as it provides the sequence of tasks and some quizes as many other courses by Coursera.

par David T

Mar 11, 2019

I like the CoLab Intro, and basics of Keras. But I think the 1st course are a bit too basic for someone who took the 5 courses Deep Learning Specialization. And it is too fast for someone who had not taken the DL courses. I would like the instructors to go over these topics in future courses:

1) TensorBoard and how to debug a faulty model

2) TF 2.0 features (Eager execution, etc)

3) hands on example on how to fix the model if validation accuracy is much worse than training accuracy

4) LSTM models

5) how to productionize the model for real life use, like TF edge or TF.js

par Mark B

Mar 09, 2019

Often coursera courses are a bit easy / superficial. This course is a bit too much so. There's just not enough meat-on-the-bone for my liking. The instructor came across very well, the material is polished and professional, there's just not enough material for me to think of this as being a course. It only takes about an hour to do each weeks' material; the programming examples provide almost no challenge. As a first course on the topic this might be okay, but if you've done anything in this space before then it will be too easy. The course also uses the highest-level TensorFlow APIs; in a sense I wonder if this is really about TensorFlow when that same API is usable with other frameworks. I hope the rest of the specialisation has more detail.

par William W

Mar 10, 2019

Very good and concise introduction to tensor flow. Important parameters to methods are explained so they are understood and no longer mysterious. The course starts with a very simple "Hello World" type model and builds to a more complex CNN. During this evolution, the code becomes necessarily more complex but the additional methods are explained as they are introduced.

par Ekwoge E B

May 12, 2019

I had a great time going through this course. I had a lot of challenges but which made me love the course even more. While I'm excited to start the next course, would still like to go through certain areas of this course to get a better grasp on some areas. I'm grateful to Cousera for such a learning opportunity!

par Raul D M

Apr 14, 2019

Even if this course it is an introduction to TensoFlow, it is too easy. Good resources and good notebooks, the lectures are not bad and well explained, but the examination part is too soft.

par Sebastian R G

Jun 12, 2019

Es un excelente curso para todo aquel que este interesado en las ciencias de datos y la inteligencia artificial ya que Tensorflow y Keras son herrameintas que acortan mucho el camino de desarrollo.

par Stephen F

Jun 07, 2019

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

par Abdallah A E M W

Jun 07, 2019

An awesome practical course that helps me to start creating my first neural networks using keras in such great methods, the instructor is very good at delivering the knowledge he has


par 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.

par Daniel M

May 15, 2019

Nice course with some flaws. It’s a course in Keras with Tensorflow under the hood but you won’t see it. It’s great it’s Keras, however the title of the course is misleading. The videos are only a few minutes per week. Mostly it’s self-study on Google-Colaboratory. If you have no clue about Python or Machine Learning you might quickly be overwhelmed by the coding involved. If you have knowledge in Deep Learning you can earn this certificate within a few hours just by answering the (rather simple) quizzes even without watching the videos because the programming assignments are not graded. The course doesn’t have the depth of the Deep Learning Specialization by Andrew Ng but Keras is a great Deep Learning Library

par Rana T J

May 14, 2019

The assignments need to be polished. They were very lackluster and non-rewarding.

par ashirwad s

May 12, 2019

I have completed this course lately and trust me this is a wonderful course which is not just well developed and designed but has also been quite understandable to noobies of Tensorflow.All the coding done in the course was explained in a very simple and elegant way. Thanks Laurence Moroney and Andrew Ng for coming with such an amazing course.

par Guillaume G

Apr 23, 2019

Ce cours balaye les fonctions de bases de la librairie d'abstraction Keras et permet de construire rapidement des réseaux de neurones complexes.

par Lu A

Apr 23, 2019

It's relatively simple course if you've already finished Andrew Ng's deep learning specialization

par Abhilash S

Apr 18, 2019

This course is good at what it's meant to do, introduce the fundamentals. Would love to see more of Tensorflow 2.0 in an improved version of this course.

par Yash P

Apr 07, 2019

An amazing start to someone looking to learn AI !

par Philip D

Apr 06, 2019

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

par Suddhaswatta m

Apr 05, 2019

Please add learning rate reduction in basic course.Thanks !! in advance

par Alon L

Mar 19, 2019

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

par Luiz C

Mar 17, 2019

it's really an introduction

par changqing_nick

Mar 12, 2019

I think it is pretty good to people who are not familar with keras

par Samarendra P

Mar 11, 2019

Excellent set of videos and practice assignments!

par Frank L V

Mar 10, 2019

This was great. I can't think of two better presenters for this topic!