Chevron Left
返回到 Deep Learning with Keras and Tensorflow

学生对 IBM 提供的 Deep Learning with Keras and Tensorflow 的评价和反馈

4.4
1,011 个评分

课程概述

Deep learning is revolutionizing many fields, including computer vision, natural language processing, and robotics. In addition, Keras, a high-level neural networks API written in Python, has become an essential part of TensorFlow, making deep learning accessible and straightforward. Mastering these techniques will open many opportunities in research and industry. You will learn to create custom layers and models in Keras and integrate Keras with TensorFlow 2.x for enhanced functionality. You will develop advanced convolutional neural networks (CNNs) using Keras. You will also build transformer models for sequential data and time series using TensorFlow with Keras. The course also covers the principles of unsupervised learning in Keras and TensorFlow for model optimization and custom training loops. Finally, you will develop and train deep Q-networks (DQNs) with Keras for reinforcement learning tasks (an overview of Generative Modeling and Reinforcement Learning is provided). You will be able to practice the concepts learned using hands-on labs in each lesson. A culminating final project in the last module will provide you an opportunity to apply your knowledge to build a Classification Model using transfer learning. This course is suitable for all aspiring AI engineers who want to learn TensorFlow and Keras. It requires a working knowledge of Python programming and basic mathematical concepts such as gradients and matrices, as well as fundamentals of Deep Learning using Keras....

热门审阅

TJ

Feb 23, 2022

I expected some more explaination for the concepts. However from tensorflow website, more could be learnt.

RR

Jul 25, 2020

Nice course to introduce you to more advanced neural network algorithms, I wish the evaluations were more challenging and based on practical exercises... there is no final assignment either.

筛选依据:

101 - Deep Learning with Keras and Tensorflow 的 125 个评论(共 220 个)

创建者 Hossein J

Jul 2, 2024

Really useful

创建者 oyenola p

Jul 13, 2022

great course

创建者 Luis C M R

Feb 23, 2022

Really clear!

创建者 Branly L

Apr 27, 2020

Very Good..!!

创建者 alireza r

Mar 21, 2025

game changer

创建者 Aditya M P

Dec 8, 2020

Good Course

创建者 Samira G

Jun 1, 2020

Love it....

创建者 Mauricio D

Jul 30, 2025

Buen curso

创建者 Gift S

Jul 24, 2024

it is best

创建者 Victor M C

Jun 30, 2024

BUEN CURSO

创建者 Sultan N Q P

Aug 2, 2025

Thank you

创建者 Sandipan C

Aug 28, 2021

Nice Info

创建者 Nikhil K

Sep 25, 2024

dqqqddwd

创建者 Amritpal K D

Oct 21, 2023

Awesome

创建者 Takahide M

Jan 6, 2023

Awesome

创建者 Krishna H

Apr 26, 2020

Good!!

创建者 Harmandeep S

Nov 10, 2025

nice

创建者 Zuhair I B

Apr 5, 2025

nice

创建者 01fe21bec413

Apr 24, 2024

Good

创建者 Lim S

Feb 28, 2022

good

创建者 Shaki A

Jul 7, 2025

_

创建者 Roger P

Aug 31, 2021

This is a good introduction to Tensorflow. Like all Coursera courses I've experienced to date, there were plusses and minuses.

The good side of each of these courses: * The courses cover the main concepts (building models, limitations, challenges, etc). They covered activation functions, Convolutions, width and depth of models, Gradient Descent and learning rate issues.

* The lessons don't oversimplify, but give you the tools you need to explore further on your own if you wish.

* Replies to my forum questions were actually surprisingly quickly answered. I was expecting the forums to be filled with months-old unanswered questions.

* Being able to replay videos was invaluable.

The less-good side:

* The exams are token, often multiple choice with unlimited retries. That is fine.

* The lessons are often replete with misspellings, grammar errors and ambiguous quiz questions.

* Sometimes, due to the stochastic nature of ML models, the errors/mispredictions differ between the Grading Rubrics and legitimately obtained results.

Would I do it again? My answer is this- I feel for six courses I have the equivalent of one junior-level semester survey course's worth of information and experience. However I was able to do it on my own time starting immediately, at my own pace, replaying the lectures at will and all for a tiny fraction of the cost and time of a college course. I do believe I have a starting point to pursue more advanced topics and for that I believe it was well worth it.