The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering hidden structures within this type of data. In this course you’ll use TensorFlow library to apply deep learning to different data types in order to solve real world problems.
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IBM課程信息
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中級
完成時間大約為13 小時
英語（English）
字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）
可靈活調整截止日期
根據您的日程表重置截止日期。
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
中級
完成時間大約為13 小時
英語（English）
字幕：法語（French）, （歐洲人講的）葡萄牙語, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）
提供方
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 5 小時
Introduction
In this module, you will learn about TensorFlow, and use it to create Linear and Logistic Regression models.
完成時間為 5 小時
5 個視頻 （總計 28 分鐘）, 1 個閱讀材料, 5 個測驗
完成時間為 2 小時
Supervised Learning Models
In this module, you will learn about about Convolutional Neural Networks, and the building blocks of a convolutional neural network, such as convolution and feature learning. You will also learn about the popular MNIST database. Finally, you will learn how to build a Multi-layer perceptron and convolutional neural networks in Python and using TensorFlow.
完成時間為 2 小時
3 個視頻 （總計 22 分鐘）
完成時間為 3 小時
Supervised Learning Models (Cont'd)
In this module, you will learn about the recurrent neural network model, and special type of a recurrent neural network, which is the Long Short-Term Memory model. Also, you will learn about the Recursive Neural Tensor Network theory, and finally, you will apply recurrent neural networks to language modelling.
完成時間為 3 小時
4 個視頻 （總計 22 分鐘）
完成時間為 2 小時
Unsupervised Deep Learning Models
In this module, you will learn about the applications of unsupervised learning. You will learn about Restricted Boltzmann Machines (RBMs), and how to train an RBM. Finally, you will apply Restricted Boltzmann Machines to build a recommendation system.
完成時間為 2 小時
2 個視頻 （總計 10 分鐘）
審閱
來自BUILDING DEEP LEARNING MODELS WITH TENSORFLOW的熱門評論
由 RR 提供2020年7月25日
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.
由 HJ 提供2020年5月17日
It would have been nice if the video tutorials would explain the code section as well, and if there would have been some in-depth teaching of the code part. But this course did benefit.
由 RC 提供2020年5月14日
Good an simple videos to understand the concept. The notebooks are very detailed and give a second layer of knowledge with practical example
由 ZR 提供2020年7月2日
Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!
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