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学生对 DeepLearning.AI 提供的 Convolutional Neural Networks in TensorFlow 的评价和反馈

4.7
8,215 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. In Course 2 of the DeepLearning.AI TensorFlow Developer Specialization, you will learn advanced techniques to improve the computer vision model you built in Course 1. You will explore how to work with real-world images in different shapes and sizes, visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including augmentation and dropout. Finally, Course 2 will introduce you to transfer learning and how learned features can be extracted from models. 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....

热门审阅

MH

May 23, 2019

A very comprehensive and easy to learn course on Tensor Flow. I am really impressed by the Instructor ability to teach difficult concept with ease. I will look forward another course of this series.

CM

Apr 30, 2019

A patient and coherent introduction. At the end, you have good working code you can use elsewhere. Remarkably, the primary lecturer, Laurence Moroney, responds fairly quickly to posts in the forum.

筛选依据:

451 - Convolutional Neural Networks in TensorFlow 的 475 个评论(共 1,269 个)

创建者 Max W

Dec 2, 2019

Excellent structure and code alongs with great examples!

创建者 WERE, D W

Aug 14, 2019

An awesome opportunity to learn CNN and its application.

创建者 Abhinav t

Jan 25, 2024

A Great course for Tensorflow certification preparation

创建者 Bruno R S

Jan 24, 2023

Good introduction to convolutions in a practical sense.

创建者 Isaac A A

Aug 5, 2020

The concepts are quite straightforward and enlightening

创建者 Vinh T

Jun 6, 2020

Thank you very much. This course is very useful fro me.

创建者 Julian R

Apr 11, 2020

Muy buen ! Cubre lo fundamental y tiene ejemplos claro!

创建者 Vineet K

Apr 11, 2020

Content and assignments were very relevant and helpful.

创建者 Mukkul K

Nov 22, 2019

Very nice course. I learned many wonderful techniques.

创建者 Louis B

Nov 19, 2019

Nice because very quick to have good efficient basics !

创建者 shweta s

Jul 16, 2019

very good content and every point are explained nicely.

创建者 Tan C T

Apr 27, 2023

I hope you have a similar course for Pytorch framework

创建者 AMIT S

Jun 13, 2021

i learn how to handle images while creating DL models.

创建者 Missaka

Mar 28, 2021

Explained everything very clearly, easy to understand.

创建者 Guillermo R

Oct 31, 2020

Good course for computer vision, challenging exercises

创建者 Eduardo J M G

Sep 17, 2020

An excellent course to keep learning about AI and DNN.

创建者 Juan E R

Jul 30, 2020

excellent course, great techer, all concepts explained

创建者 MOINUL I

Jul 26, 2020

Great explanation of everything. I have learned a lot.

创建者 Kevin R

Apr 29, 2020

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ce teaches simple and convincing.

创建者 ongole s s

Apr 21, 2020

learnt how to work on real projects in computer vision

创建者 chitresh k

Feb 5, 2020

Loved the content and depth of the materials discussed

创建者 Walid A

Aug 16, 2019

The Course is too easy but it was fun and to the point

创建者 채현석

May 7, 2023

It's very useful for me to learn about CNN. Very Good

创建者 Farhodbek S

Dec 6, 2021

Very useful corese for learning Tensorflow framework

创建者 ROHIT B

Nov 26, 2021

BEST EXPLAINATION OF TRANSFER LEARNING AND TENSORFLOW