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Avis et commentaires pour d'étudiants pour Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning par deeplearning.ai

4.7
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16,308 évaluations
3,391 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 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....

Meilleurs avis

AS
8 mars 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 août 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 sur 3,412 Avis pour Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

par Michael B

31 juil. 2019

FANTASTIC!

I love the courses put out by deeplearning.ai. I previously took the 5 course deep learning sequence taught by Andrew Ng (which I would also recommend), and am VERY pleased with the first course of this sequence taught by Laurence Moroney.

The lectures are broken into small, digestible chunks. The quizzes are hit core knowledge points w/o any tedious "can you do this by hand" nonsense you see in some other courses. The notebooks provided in the course offer useful templates for adapting to other problems. Just amazingly well done in every aspect.

Looking forward to taking the rest of the sequence!

par Pushpak G

25 août 2020

Excellent for any beginner. Watching Andrew Ng anywhere gives you a sense of authority and validates everything. But all the teaching part is done by Lawrence who is equally humble and knowledgeable.

All the theoretical topics covered are explained in brief but there are ample resources on the internet to understand them thoroughly.

The coding part is very easy to follow.Although some python code blocks were typical to understand but again you can always look them up on the internet.

Overall it is a brilliant course for anyone who wants to start with Keras, tensorflow, deep learning.

par Prafull P

9 nov. 2019

This course is an excellent starter for people who want to learn about Tensorflow and how to use it to create neural network model very quickly . The Instructor explains every thing in very lucid language.Course is well organized to help you go from beginner to an intermediate quickly. Great articles and videos links will also come your way so even that would help you improve and enhance your knowledge. Highly recommended for someone who wants to learn about Tensorflow and enter into the field of ML & AI. A Big Thanks to deeplearning.ai for creating such course :)

par Anirban S

18 nov. 2020

I love the following things about the course:

a. Very calm, consolidated, and well thought of introduction to TensorFlow. The documentation could be a little intimidating for a newcomer. But this course is a step by step guide.

b. The exercises encourage you to explore more. When you explore more, you learn more.

c. The workload is just enough and you can manage it with your regular course studies and student jobs.

What I wish I had a little more from this course:

a. I wish there was some element of NLP in this course. A little would have helped.

par Victor A

10 sept. 2020

Great learning experience overall... Prof. Moroney was very patient in his approach and took his teaching one step at a time. So I never felt like I was taking too huge a leap at any particular one time. The links he provides for study were also helpful.

It was obviously a plus to have a great teacher like Andrew NG chip in occasionally a word or two.

Overall, it's a great course and I'd absolutely recommend to anyone interested in exploring the possibilities that computers of today give us in exploring our world.

par Kirt U

22 juil. 2020

The course material and presentation is excellent. However some of the course tools are complete trash (code autograder in particular - this is because the code that was shipped off to the code autograder wasn't the code I had been working on - it wasn't until later that I realized that the tools were taking predefined [expected] file names and not the code I was working on - this is only year 8 of this otherwise excellent project - 8 years and the tools are still substandard). Also the quizzes are too easy.

par Dipankar R D

19 déc. 2020

When I joined this course, I did some basic projects with tensorflow. But they way Mr.Laurence Moroney took me going through every details of codes,and sharing the ideas and concepts why we use this, when we use that etc., I was so encouraged that I've spent hours to tune the parameters etc. Hats off to deeplearning.ai that I'm able to learn from the experts. At last but not the least, Prof.Andrew Ng has always been an inspiration to me and I'm grateful that he motivates me always by teaching AI like stories.

par Hannan S

27 oct. 2019

First of all, the course was amazing! I found it great for the following reasons:

- Laurence Moroney (Instructor) was very professional and clear while delivering the knowledge

- The introductions by Andrew NG were really nice

- Easy to understand codes and understanding of thr underlying principles

- Varied topics such as CNN, NLP & Time Series

- Very insightful by providing expert opinions about different ways of model optimization

I really enjoyed the course and I thank the instructor for the same :)

par Curtis P

26 juil. 2020

Coursera and of course the instructors have really got this online teaching down to a science allowing students to cover often quite complex topics in an easy to digest and efficient manner. Even though it does skim the surface it does give a very good 10,000 foot view of the objectives and capabilities of the topic and technologies. To get same perspective on my own would be a lot of googling, trial and error, without the benefit of knowing 100% that I was covering the appropriate knowledge.

par Pranav B

5 juin 2020

Introductory level course. Perhaps the best feature of this course is that you start to learn by doing right from week-1. The instructor doesn't spend time explaining every line one by one with every detail. That leaves you to figure out a few things on your own due to which you're bound to remember these details. Notebooks are also much better than the deep learning specilaisation. I often found myself going through the tensorflow documentation - learning and exploring as I did. Fun course!

par Gilles P P

8 mars 2020

Cours intéressant, clair et facile à comprendre. L'enseignant est très sympathique et semble passionné. C'est également facile à comprendre même pour un non english native speaker.

J'ai déjà suivit les cours d'Andrew Ng et comme de nombreuses interview d'Andrew et des références sont données dans ce cours cela les rends très complémentaire.

On a qu'une envie c'est de continuer pour en prendre plus sur ce sujet passionnant.

Je suis très satisfait de suivre cette spécialisation

Gilles Pierre

par Rushikesh J

27 mars 2020

Perfect Course, It tells you how to implement basic neural network to deep cnn.

Week 1 : Intro to tensorflow/keras

Week 2: building dense neural network; 2 applications fashion mnist and digit mnist

week 3: building cnn, improving accuracy on week 2 applications

week 4: using image generator to auto label the images, horse/human classifier and happy/sad classifier

Overall a perfect course to begin with, though i would advice to have basic understanding of neural network and its working.

par Matthew E

23 oct. 2019

Although the concepts can be a bit technical, the explanations are very accessible. You learn how to implement ideas instantly, and by the end of the course, you are very well suited to experiment on your own. I'll be continuing the specialization. This, together with the deep learning specialization (which I have already taken) will I believe fully prepare anyone to work or do basic research in this field (at a fraction of the cost of a CS or AI undergraduate degree). Fantastic!

par Sripathi S

21 janv. 2020

Very well structured course to get started with Deep Learning using TensorFlow. Laurence explains the flow of the programs and key concepts in a clear manner, which made it easy for a beginner like me to get familiar with the material quickly. Working through the problems without getting stuck in the theory was a fun way to see the possibilities of AI first hand and learn by doing. Highly recommend this course for any developers or programmers who want to explore deep learning.

par HE Y

28 juin 2020

This course should be considered as the inception of the Tensorflow when one steps into the field of deep learning. That would be very helpful to build a comprehensible network about this famous framework and how AI is applied to real life. I suggest introducing more practical work, for example, the video in the course, how AI helps the Africain farmers to know the health state of their crops. Using this case as an example might be more exciting from my point of view. Thanks.

par Yash P

25 déc. 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!

par Rishi G V

19 juin 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.

Thanks.

par Dhruv D

16 janv. 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

par Ahsun T

18 févr. 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!

par Oscar O N

24 oct. 2021

The course allows you to get closer to TensorFlow for the first time. You end up training a model using real-world images and convolutional neural networks. The instructor is very clear in the explanations, and the course material allows you to learn in an accelerated way. You go from the simple to the complex. Videos are short, clear, and to the point. If you have a background in neural networks, you will take better advantage of the course.

par Sourav S

25 oct. 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.

par neil h

9 juil. 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.

par Mateus d A D P

27 sept. 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.

par Alejandro D G

6 mars 2021

Great practical course. I think that if you don't have the background of Deep Learning (that is given in other Deeplearinng.ai 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.

par Xiaonuo G

9 mai 2020

Using https://colab.research.google.com/ 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.