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Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, deeplearning.ai

4.7
163 notes
32 avis

À propos de ce 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 Specialization 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. The full deeplearning.ai 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

par 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?

par CG

Mar 09, 2019

without a doubt, Laurence's teaching is much better than reading the documentation! The course is a great starting point!

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37 avis

par Jochen Röth

Mar 20, 2019

it's to easy and to shiort. Not even programming assignments were evaluated

par Khaled Alhendi

Mar 20, 2019

This was great!! Learned and practiced ML

par Walter Gordy

Mar 19, 2019

This is a great introduction to Keras, and I learned about some unknown features. Unfortunately, I had thought it would be more focused on Tensorflow, since it's in the title of the course. I had decided to take this course midway through the Deep Learning specialization. I was hoping to gain more practice with easier Tensorflow examples, but the course didn't cover any core Tensorflow.

par Alon Lavian

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)

par BRIAN S HENRY

Mar 19, 2019

A very effective and clear introduction to Tensorflow and AI, ML & DL.

par Abdoulaye Diallo

Mar 18, 2019

Good introduction

par Ben Barnard

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 Luis

Mar 17, 2019

it's really an introduction

par Alexander Berger

Mar 17, 2019

I liked the course as it is practice oriented, but 4 weeks is too long for it. 2 weeks would be more than enought.

par polisetty sumanth

Mar 16, 2019

Very Informative. Good for Beginners to Tensorflow