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Convolutional Neural Networks in TensorFlow(으)로 돌아가기

Convolutional Neural Networks in TensorFlow, deeplearning.ai

4.8
104개의 평가
14개의 리뷰

About this Course

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 upcoming Machine Learning in Tensorflow 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 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. The full deeplearning.ai TensorFlow Specialization will be available later this year, but you can enroll in the first two courses today. We recommend starting with Course 1: Introduction to TensorFlow for AI, ML, and DL....

최상위 리뷰

대학: CM

May 01, 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.

대학: RC

May 15, 2019

Excellent material superbly presented by world-class experts.\n\nSorry if this sounds sycophantic, but this series contains some of the best courses I've encountered in50+ years of learning.

필터링 기준:

14개의 리뷰

대학: Paweł Dudzic

May 15, 2019

Pretty basic level, aimed rather to beginners.

대학: Romilly Cocking

May 15, 2019

Excellent material superbly presented by world-class experts.

Sorry if this sounds sycophantic, but this series contains some of the best courses I've encountered in50+ years of learning.

대학: Zeev Shilor

May 14, 2019

Clear, concise, well designed

대학: Edir Garcia

May 11, 2019

It's great to learn about data augmentation techniques and how to implement this. This is a great complement for the deeplearning.ai's course on Convolutional Neural Networks.

대학: Raffaele Grandi

May 10, 2019

Great course! I can't wait to going further and deeper. Thanks

대학: Nick Allen

May 08, 2019

This course significantly lacks depth. The topic is covered at a very high-level and represents only a lightweight introduction. You will not gain any insights into the challenges that someone might face using CNNs on Tensorflow in a real-world scenario.

This course does not compare to the kind of insights that you learn from the other courses taught by Andrew Ng.

There are no graded programming assignments to validate what you have learned. The exercises that are provided are very simplistic.

대학: Ivelin Ivanov

May 05, 2019

Many thanks to Andrew Ng and team for the great balance of theoretical background, practical references and hands-on programming exercises.

대학: Hoang Minh Nhat Tran

May 04, 2019

It's a perfect course to learn TensorFlow for CNN, and it is extremely easy to understand. Thank you very much!

대학: Heman Kodappully

May 04, 2019

I enjoyed doing this course on CNN in Tensorflow. Thanks for the lectures by Laurence Moroney. And it is always a pleasure to hear Andrew Ng explain even difficult concepts in simple terms. He is one of my favorite teachers online, and reading about his ML course in a New York Times article back in 2012 or 2013 made me completely change my career direction and motivated me to eventually get into cloud and Big Data! And thanks also for the exercises on codelab. That makes it really convenient to learn and experiment with Machine Learning and Deep Learning.

I did take the first course in the Deep Learning Specialization early last year, but didn't get a chance to do this until now. Looking forward to completing the remaining three courses sometime this year.

대학: Dmitry Sherbina

May 03, 2019

Consize notebooks. Clear explanations