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Convolutional Neural Networks in TensorFlow, deeplearning.ai

4.8
(оценок: 109)

Об этом курсе

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....

Лучшие рецензии

автор: 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.

автор: 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.

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Рецензии: 17

автор: 田亮

May 20, 2019

this class is not difficult ,it is suitable for benginers of DL

автор: Subhadeep Dash

May 20, 2019

Very brief and precisely taught implementing various techniques in Convolution Neural Networks by using Tensorflow. Quite time saving and a good one to boost your skills.

автор: Na

May 20, 2019

Thanks Mr. Moroney! But the course is a little easy.

автор: Paweł Dudzic

May 15, 2019

Pretty basic level, aimed rather to beginners.

автор: 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.

автор: Zeev Shilor

May 14, 2019

Clear, concise, well designed

автор: 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.

автор: Raffaele Grandi

May 10, 2019

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

автор: 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.

автор: 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.