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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

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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 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

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?

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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126 - 150 de 3,379 revisiones para Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

por Yash P

25 de dic. de 2020

I have no words for expressing my feeling of immense gratitude towards Laurence Moroney, Andrew Ng, and all other DeepLearning.AI and Coursera team for providing us with these invaluable courses and your priceless time. I am thankful to Coursera for supporting us who aspire to get educated by such intelligent people and technocrats by providing us with financial aid. This is a great course, and I strongly recommend it to everyone who is reading my review. Thank You So Much!

por Rishi G V

19 de jun. de 2019

The author, is way of teaching make me understand more into the fundamentals of the concepts. Now i have the strong understanding of these concepts with Good hands-on-experience.

But the current course i only audit, because of financial problem. If you provide me certificate for completion of these course it will be definitely useful for my career goal.

My leaning never going to stop , hereafter i will learn lot of courses from coursera with the financial aid.


por Dhruv D

16 de ene. de 2021

I've read textbooks, done about 9 months of professional AI consulting and done other courses in AI/ML. this is by far the best I have come across so far, it flits over the details intentionally and slowly feeds them to you as you need them so you can best understand them. Also you get HEAPS of real world examples shown along the way. The culmination of this is a solid foundation and a fun course with awesome assessments and lectures that builds PRACTICAL knowledge

por Ahsun T

18 de feb. de 2020

Although while pursuing a higher degree in AI it was great to learn the minutiae of machine learning methods, this course seems to provide the best abstraction for a high level programmer - giving flexibility to play around with different datasets and GPU architectures and making it super intuitive and easy to apply it to your own problems. Let's build AI for solving problems where human decision making is limited It's really cool and you can make a difference!

por Sourav S

25 de oct. de 2020

This course was very useful, especially if you gone through the deep learning specialization, which I did. The course starts with implementing a simple neural network, and then progresses onto convolutional neural networks. The course ends with a very useful data management topic on training data labelling. I would have found it useful if the course also focused on alternative attributes for the some of layers like Conv2D, the compiler, etc.

por neil h

9 de jul. de 2019

Very well-balanced presentation. Started considerable fluency in python, advanced education in digital-signal processing, but limited experience with ANNs in general and tensor-flow in particular. With this course — and some background in Dreyfus 2005 and Haykin 2009 — I feel like I'm starting to get the picture. The hands-on was straightforwardly presented and extensible, with just enough wrinkles to make you think and stump the chumps.

por Mateus d A D P

27 de sep. de 2020

This was a great course to learn how to use the basics of Tensorflow. The layers mentioned in the course are Dense (fully-connected layers), Convolutional, Pooling and Flatten layers. It also teaches you how to use callback functions during the training phase, as well as how to handle real-world images.

This course does not teach you about how to tune hyperparameters, but I wouldn't expect that from an introduction course.

por Alejandro D G

6 de mar. de 2021

Great practical course. I think that if you don't have the background of Deep Learning (that is given in other specialization, the Deep Learning one, which I really recommend), is better to understand first the concepts before doing this course. But if you have the concepts, and understand how this NNs work, this is a great place to learn how to put in practice all this with the Tensorflow's Keras API.

por Xiaonuo G

9 de may. de 2020

Using is definitely a good choice because it saves the learners a big chunk of time setting up a deeplearning workstation by herself. The course's source code is commented extensively to ease understanding. Although the technical details and specific explanation of the deeplearning algorithms are pretty lightweight, it's more than enough to get one's hands dirty as a beginner course.

por Dina M

16 de nov. de 2020

I really enjoyed the line-by-line code explanation and the right balance between theoretical and practical parts. As a beginner, it is easy to get lost in all different types of layers, optimisers, etc, and this course helps understand a general structure of a neural network program. The Python notebooks that we are given are extremely useful for watching how the things work by experimenting with code. Thank you!

por Neel M

24 de jun. de 2019

This is an amazing course, and one can feel the hard work they have put into it. I was able to experience so much theory in practice, image augmentation, dropouts, transfer learning. Learning experience? Much better, it was a learning enthrallment! This is one of those courses which make deep learning looks so easy, and approachable. Highly recommended for anybody, and coursera should have more courses like this.

por Tamim-Ul-Haq M

28 de sep. de 2020

Very interesting start to TensorFlow. This course although doesn't teach the basics of a ML model (which Stanford's ML course and the Deep Learning Specialization already do in great detail) but gets right down to how you can use TensorFlow for classifying what type of problem such as the basic regression problem to an image classifier. This course offers intuitive on how to properly use TensorFlow.

por Ilias L

4 de jul. de 2020

Enjoyed the visualization part where we were encouraged to peek at different parts of the neural networks to understand how features were created.

Could be somewhat more thorough on how different amount of layers and architectures affect the quality of features created and the overall performance instead of encouraging people to just play around.

Useful, to the point and easily digestible intro to TF

por Poornima R

23 de mar. de 2019

I loved how this course is structured. I'm right now preparing for my interviews and this course had concepts explained in like awesome way that you could use to answer in interviews. The google colab platform was very helpful and tutor Prof.Lawrence was incredible at explaining the codes line by line. On the whole, I would go over this course over and over again to get my concepts at fingertips.

por Daniel M

27 de may. de 2020

If you just make this Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning Course you can manage to make a few simple codes.

This introduction complements very well with Deep Learning Specialization. In case you have done the specialization, this course will give you the first steps so you can start programming and learning for more complex applications.

por Cheng-Tsu Y

28 de may. de 2020

Great course for starting the implementation of classification model on Keras. Although more detail into theoretical part should be found from other courses or materials, this course definitely provides the very first step in the coding part. For me, with little prior knowledge in python, I did learn a lot by studying the Notebook sample code carefully. So I will recommend this course!

por Timothy Q

13 de nov. de 2020

If you're looking for a more theoretical approach, go take Andrew Ng's Deep Learning Specialization first. This course is more of a crash course based from what Andrew has already discussed, and is heavily focused on hands-on application using Python. The course will encourage you to experiment and understand the impact of different parameters in your model. It's fun and challenging.

por Shubhangi S

30 de ago. de 2020

The learning process is very explanatory and very easy to understand. the course has many quizzes and programmable problems which allows the learner to get a clear view of how to work with TensorFlow. the course also provides various notebooks where you can experiment by changing the values of variables and see the effect of it in the output which in turn makes the learning valuable.

por Abdulaziz A J

19 de mar. de 2020

I am planning on taking TensorFlow certificate, so I finished this course in 5 days. Glad I did that as I did lean how deep neural nets and convolutional neural nets work! I am still in the beginning of my path, so I will keep working hard to finish all of the other courses in order to achieve TensorFlow certificate. Thank you, Laurance and Andrew, for the amazing beneficial course!

por Erling J

26 de jun. de 2019

Elegant and efficient introduction to the plug-and-play Google Colaboration application that let's you easily write and execute Python code in the cloud, as well as the Keras API that let's you access the Tensorflow package to use with convolution and pooling layers. The exercises were brilliant as well and I have high expectations about the following courses in the specialization.

por Κώστας Π

17 de ago. de 2021

A quiet interesting course that introduce you to TensorFlow, and gives a basic understanting of image processing in Python. The course was well organized with explanatory videos, code scripts in google collabs, and necessary assignments to practise your code skills. Overall I am very pleased that I attended this course, and I am planning to attend more like this in the near future

por Christian D M

23 de ene. de 2021

Concise and cohesive course, and was very easy to follow! It was nice to see both the theoretical and practical concepts explained in a manner that a beginner such as myself can understand. They provide many other resources in case I get stuck or need further explanation as well. Thank you for a great introductory course, and I am excited to learn more in the future courses.

por Sohail Z

22 de jul. de 2019

Great intro by Laurence, very comprehensible. But i think a bit more work should have been done on presentations for deep learning newbies for them to be able to grasp the concepts of difficult topics like convolutions.

Though i would recommend anyone to first complete Andrew Ng's deep specialization first, then start this course, it would be really beneficial.

por Abhinand

28 de mar. de 2020

I think this is a great introduction to Tensorflow 2.0 as a whole. What other reviews may say is that they didn't go into much of the theoretical aspects, yeah that's fine after all this is a course that is meant to be practical by all means. For people who've already taken Andrew's Deep Learning Course for example.

I think the instructor has done a great job! 5 stars!

por Abhishek D

5 de jul. de 2020

Liked the course as it did not spoon feed you the answers and you had to go back and watch the videos again to attempt the programming assignments. Overall it was fun learning tensorflow. I am very excited for the next course in the specialization. I would encourage people to do the entire specialization because this course alone wont teach you much about tensorflow