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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

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2,785 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
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?

RD
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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151 - 175 de 2,773 revisiones para Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

por Akshit A

22 de jun. de 2020

The course and the teaching style of Dr Laurence Moroney combine both taking baby steps and working with code together, which works really well for me. I've tried a lot of different courses/ tutorials but it's either they dive into code too deep or they dive into theory too deep. This one however does both but increases gradually.

por Deepak V

26 de abr. de 2020

This course very quickly made me appreciate the use of convolutional neural networks in computer vision. It focuses on the use of a few functions available in Tensor Flow and Keras for deep learning without going too much into the algorithms that power them. This makes it an excellent starter course in deep learning using python.

por Tobias L

23 de oct. de 2020

Nice introduction to Tensorflow, Callbacks and Convolutional Layers. As this is a course on intermediate level, I recommend you take the ML and Deep Learning courses by Andrew Ng first. With the knowledge from these courses you will get way more out of this one (which then is just what it says: An Introduction to Tensorflow).

por Deepankar K A

17 de sep. de 2020

I loved the course from the very beginning. The structure of the course is well designed for a student like me. Instead of making long videos on a topic, each video explains only a small topic and is 4-5 minutes long. Special thanks to the class instructor Laurence Moroney who explained advanced topics so quickly and clearly.

por Артём А

29 de jul. de 2020

The course is really great! Besides containing loads of useful information and being totally ML-novice friendly it has a huge amount of links giving a better understanding the ideas under the hood and practical implementations of knowledge! Quiet sure that the further parts of specialization are of the same high quality!

por Leonardo I

22 de ago. de 2019

A very well structured course that introduces the learner to the basics. The instruction is clear, exercises are easy to follow. You can see that the instructors have put a lot of thought into the design of this course I enjoyed every minute of every video and every line of every exercise. Thanks, Andrew and Laurence

por Romilly C

23 de abr. de 2019

A very well-presented, well-structured course with a good balance of theory and practice. It was fun, and I learned a lot.

The two presenters both have a warm style and a deep knowledge of the subject.

An excellent starting point for Python-literate developers who want to get to grips with TensorFlow and Deep Learning.

por Dinesh P

11 de abr. de 2019

I really liked the way the mentor went through the course. I believe there is till a lot to learn about tensorflow and deep learning and i am looking forward to the next courses ! I also want to say thanks to the mentors for providing my scholarship because i won't be able to study and enjoy this course without it!

por Ronny K O

10 de ago. de 2020

A while back I chose to do Java over Python because I thought it was easier. Looking back now, I realise that it is the other way around. I have learned about Tensor flow and Convolution Neural Networks and as it turns out, Python is 10 times easier than Java. I am glad I tried out this course.

Thanks a lot Coursera

por Jonathan P

25 de ene. de 2020

I liked the course very much!

It is definitely required to know python quite well and would be good if one had a liitle bit of pre-knowledge in the field of ML / Stat or equivalent.

Everything was very well explained, the exercises had exactly the right amound of complexity and I never felt "lost" during the course.

por Pratik M

31 de may. de 2020

The tutor Laurence Moroney is very good in explaining Neural networks basis with Tensorflow. I highly recommend this course to any individual planning to become ML Engineer. I would still look up for indepth study on some topics like knowledge on when to use different number of ConvNet filters (eg. 16, 32, 64 etc)

por Shilin G

18 de jul. de 2019

I think this course is great, serves its purpose of introducing TensorFlow as a tool. For people who are looking for more in-depth knowledge of deep learning, you should go for a proper deep learning specialisation. This one is great for people who already know something about deep learning but new to TensorFlow.

por Melwin J

26 de abr. de 2020

it gave a very good introduction to tensorflow . i realy like the course. I had spent a lot of time learning algorithms, working and the theory behind artificial intelligence .this course has helped me to put all what i have learned to practical use. i suggest this to all those who want to atart with tensorflow.

por shishupalreddy

6 de abr. de 2020

Very crisp and clear understanding of Tensorflow in AI , Deep learning.

Post this course I am well versed with programming paradigm of Basic NN, Convolutions, MaxPooling, Filers , CallBacks , model training,validation, prediction. Appreciate the exercises and explanations. Feeling handful of experience with it.

por Artem D

20 de ene. de 2020

That was interesting and not hard, so you won't be afraid of coding =). I do not recommend to take this course if you have no theory base regarding NNs (in this case first complete DL specialization by deeplearning.ai). This course is high-level, expecting more of deep dive in the following courses =). Peace!

por Jian C

13 de may. de 2020

Solved a lot of my problems that come up to me when I read the code written by other people in Github/Kaggle. I have taken ML course with python. (no framework) This would be a great material for someone like me who know some ML and don’t know Tensor-flow. You can go over the whole course in just 1-2 days.

por meet d

20 de nov. de 2020

This course provides knowledge about Tensorflow APIs, not the fundamentals of Deep Learning. So, I highly recommend learners to complete Deep Learning Specialization course offered by Deeplearning.ai first. This course will refresh all the concepts. Course covers all the scopes for what it is developed.

por Mathis V E

27 de dic. de 2019

For someone new to AI/ML, this is a good place to start. If you're already familiar with deep neural networks, conv nets, ect (as explained in Andrews Deep Learning specialization) this course will be a breeze, but it will teach you how to use tensorflow as intended. I did this course in about 3-4 hours.

por Ishwar N

15 de abr. de 2020

The best practical oriented and hands on course on Tensorflow, highly recommended. Laurence Moroney (Google) is a great teacher, love his pedagogy, he does not delve too much into mathematics and still makes concepts very clear, because of this I could finish the course in 3 evenings instead of 4 weeks.

por Rodolfo V d A

29 de jun. de 2020

I loved this course! Thanks to Professsor Moroney for his excelente lectures.

(If a could contribuit with some thing, maybe more exercises and few more explanations about the parameters on function. Of course, wether the explanation on parameters come in futures course, please desconsider my comment. )

por Omar R L

13 de mar. de 2020

Great course, I was really interesting. Just one thing the notebooks are not well explained like we're used in the deeplearning.ai with Andrew. But no problem it makes it more challenging. Another thing, I don't know if this course is using the new version of tensorflow but I hope it's using it (2.0).

por P.sai c

6 de jul. de 2020

as a beginner i have no idea on how to implement the CNN even though i know the concepts of CNN it was hard to implement but this "Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning" gave me a basic idea on how to implement them and the tutorial was too good

por Ajay C

17 de jun. de 2020

It was short and crisp, if assignments were bit more challenging it would have been a great learning. All things to the point no hour long videos to bore us. It is recommended for beginners. For mid to expert level u can complete the whole course in 4 hours with all the reading and assignment.

por Dr. S P

7 de abr. de 2019

This course is well structured with very good instructional delivery. The vivid explanations and the discussion forum does not let you feel that you are alone. There are answers to almost all our doubts even before we post them in the forum. Looking forward for the next course in this series.

por Gulshan R

6 de jun. de 2019

This course was really beneficial for me. It helped me understand the concepts in more depth. The mentor helped a lot by creating notebooks of algorithms being explained. This truly helped in visualizing the features or what really is happening behind the training of the model. Thanks a lot.