Chevron Left
返回到 Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

学生对 DeepLearning.AI 提供的 Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning 的评价和反馈

4.8
19,705 个评分

课程概述

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 DeepLearning.AI TensorFlow Developer 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 Developer 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....

热门审阅

OS

Jan 25, 2023

I really liked the course. It was well explained and very interactive. I would like to continue the rest of the courses in the course if you allow me. Thank you. The course has been of great use to me

AS

Mar 8, 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?

筛选依据:

651 - Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning 的 675 个评论(共 4,018 个)

创建者 TEJAS P

Jun 28, 2020

An Amazing introduction to the practical applications of Deep Learning. Everything was really well explained and the course progressed in a step by step manner!

创建者 Vilhelm v E

Mar 23, 2020

Nice course and the assignments were nicely integrated and relevant. Still think it would be nice if the goal was more relevant than to just overfit every time.

创建者 Jon B

Mar 13, 2020

Awesome introduction to Tensorflow. I've taken Deep Learning theory courses, but this is my first exposure to a DL library. Looking forward to the next courses.

创建者 Antti R

Nov 2, 2019

Good exercises that were easy to follow. The jumping between Jupyter and colab was a bit annoying especially as I wanted to copy the content to my own computer.

创建者 RantingCui

Aug 9, 2019

I think this course is very practical and hands-on. The design of this course is precise and comfortable for me who is not an expert in this field. Thanks again

创建者 Mathias T

Jan 13, 2021

My goal and hope was to teach me how to use machine learning in practice. The course gave me a fast track of implementing machine learning in Colab TensorFlow.

创建者 Prantik D

Aug 2, 2020

Everything is top class from teaching to assignment or quiz, best course in internet about Tensorflow .

Thank you Instructor Laurence Moroney and Coursera team.

创建者 Sanjeev K Y

Jun 29, 2020

This specialization gives a very thorough use of the Tensorflow and after this course completion, I will be more confident about using Tensorflow for projects.

创建者 ongole s s

Apr 18, 2020

had a great experience in learning tensorflow for CNNs and very interesting to write complex algorithms in few lines of code.Thanks to coursera and instructors

创建者 Jerry H

Mar 5, 2020

I appreciated the opportunity to see how the basic codes works, and dive a bit more into the details. Does a great job of demonstrating the power of TensorFlow

创建者 hiten s

Aug 12, 2019

Amazing Course And Build The convolution and dense neural network with a fewer line of code. And Also the Learn About the Google Colab and The it's GPU and TPU

创建者 Ryan W

Jun 10, 2022

Very well done. Went from no TensorFlow knowledge to being confident I can write my own code to accomplish research tasks involving imaging in under 15 hours!

创建者 Haitham A

Aug 16, 2019

Straight forward and direct to the point. Very good pace for newbies and to refresh knowledge. It also guides to another resources for more deep understanding

创建者 HAMZA I

Feb 19, 2023

it's a great and perfect course for beginners because it lets you practice and see the results in real-life examples so that you can get a sense of the field

创建者 Akhash S S

Apr 25, 2021

This course helped me understand the fundamentals of neural networks, data preprocessing, optimizers, loss functions, normalization, and convolution filters.

创建者 Camilo A N S

Sep 1, 2020

This is an amazing course, there are too many concepts that we don't know but they do it really easy to learn. I'm definitely excited for taking next course.

创建者 Maskur A S S

Mar 24, 2023

It's a great course to start with a basic knowledge in ML or cnn. Its easy to understand and the work book really helpful where any one practice and learn .

创建者 Wing P

Sep 21, 2021

Well done overall. But some explanation of how the images are resized (i.e. cropped or squished) would be good, not to mention the pitfalls of doing either.

创建者 Anwar S

Sep 7, 2020

well designed course with simple introduction. Slowly increasing the level in assignments helps in increasesing the confidence of students at a higher rate.

创建者 SHIBU M

Aug 8, 2020

This first course was amazing. I really enjoyed it a lot. I really like the assignments. I am excited to complete the next course in this series of courses.

创建者 LUIS A D R

Jul 11, 2021

It is an extraordinary experience to have the chance to take the class with world leader in AI. I couldn't imagine to have this opportunity few years ago.

创建者 Michele M C

Feb 11, 2021

Straightforward and complete introduction to deelearning, CNN and datasets managing. I suggest this course to introduce yourself to Artificial Intelligence

创建者 tonmoy s

Nov 9, 2020

This course is so awesome to learn convolution neural network where i had never seen before. I hope, this course will change my life. Thanks Coursera Team.

创建者 Jack S

Jun 12, 2020

It was a great introduction to get hands-on training with TensorFlow 2.0 and get a taste of image recognition tasks in less than 20 lines of code. Amazing!