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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:

3951 - Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning 的 3975 个评论(共 4,018 个)

创建者 Dan G

Apr 20, 2020

The exercises are very repetitive and basically just copies of the notebooks in the course. There is no thinking required for this course. The material is very shallow.

创建者 18R11A04F1 C B

Jun 11, 2021

not to bad mouth, but this course is good yet being a beginner I don't suggest it as most of the code here is taught like alphabet that has purpose but no sense

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创建者 Laha A

May 9, 2019

I would say it is a introduction to Keras rather than Tensorflow. The course not really touch tensorflow, it all about the high level API which is Keras in TF.

创建者 Maharshi R

Sep 8, 2021

The grader is very buggy. Coded a 1-Conv2d & 1-MaxPool model and caused the grader to run out of memory. However, a more complicated model passes the solution.

创建者 Mohammed E

Apr 15, 2020

the notebooks have a poor explanation of what should be done and unless you delete the last two cells every time you won't be able to submit

创建者 ELLEUCH H

Jan 1, 2022

While useful, the experience with submitting the assignements was really inferior to what I'm used to with Coursera and DeepLearning.AI

创建者 Prantik R

Feb 17, 2021

This course needs to be more beginner friendly....it directly jumps to advanced concepts without clearing the intermediates

创建者 Matthew R

Dec 13, 2020

Really superficial overview of tensorflow and deep learning. Very few concepts were explained in any real depth.

创建者 Suraj R

Jul 18, 2019

Resources shown in the video were not included as web links, so the course couldn't be completed

创建者 Rudrani G

Aug 25, 2019

A little too complex for beginners. Content must be explained from a novice point of view

创建者 John M

Jul 5, 2020

Some reading exercises had missing links and some code used a deprecated function.

创建者 Gautam K

Jan 16, 2022

Not a great experience with the assignments, especially the last one.

创建者 Malmansoori

Jul 14, 2019

This course teach how to use Keras more than using Tensorflow

创建者 41_AI&ML_Mehul S

Mar 29, 2022

Very Easy Course. A basic course marked as intermediate

创建者 Francisco R

Apr 23, 2019

It´s well explained but way too basic and short.

创建者 Xixi W

Aug 10, 2019

这课挺水的, 不如 deep learning specialization多矣。

创建者 Alejandro D

Aug 20, 2019

notebooks need work from the instructors

创建者 Deleted A

Jul 30, 2019

Course was not rigorous enough

创建者 Reyhanssan I

Oct 28, 2024

Because the LAB is so lagging

创建者 Dhrubajyoti G

Jul 29, 2023

Too much superficial.

创建者 Reinier V

Jan 12, 2021

Too basic.

创建者 Peter C

Aug 11, 2019

meh

创建者 Maciej D

Aug 12, 2021

This course is FULL of errors (both in code and math), inconsistencies and wrong explanations. I tried to document them, but I just gave up, because it is so many of them... For example the math which explains multiclass classification (Week 2 Video “Coding a Computer Vision Neural Network”) is wrong – the output of multiclass classification should be pseudoprobabilities, not numbers ranging 1 to 9… There are also unsolved problems reported in GitHub (https://github.com/lmoroney/dlaicourse). It seems like they really don’t care about correctness, completeness and quality of this course… If you want to learn TensorFlow I highly discourage to use this course - you will just learn wrong things and would have to unlearn them later... Also graded exercises are in TensorFlow 1.x and materials are prepared for TensorFlow 2.x which means that sometimes the code from materials does not work in graded exec, eg. logs.get('accuracy') does not work in tf 1.x and you need to use logs.get('acc'). I did this course only to get some practice and pass TensorFlow exam, because I'm academic who works with PyTorch.

创建者 Yoni K

Oct 1, 2019

First of all, it's an introduction to Keras and not Tensorflow.

Secondly, the explanations the author gives are lacking/misleading.

For example,in week one the net didn't learn exactly the hypothesis 2x-1 for other reasons than the ones he mentioned (oh,and the net did not give some kind of a probabilistic interpretation to the data...).

I am not sure why Andrew NG (who is the best instructor in the world to my mind) allowed this kind of instructor to be branded as deeplearning.ai.

创建者 Anthony G

Dec 4, 2020

This course claims to be over 28 hours, however, I was able to finish it (watching every video, reading every bit of text, doing every exercise) in less than 6 hours. The lab work is a complete copy-and-paste of the examples covered in the course. If you want to "buy a credential" take this course, but if you want to actually learn anything, take another course.