課程信息
4.9
14 個評分
5 個審閱
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中級

中級

完成時間(小時)

完成時間大約為12 小時

建議:4 weeks of study, 2-5 hours/week...
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英語(English)

字幕:英語(English)...
100% 在線

100% 在線

立即開始,按照自己的計劃學習。
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可靈活調整截止日期

根據您的日程表重置截止日期。
中級

中級

完成時間(小時)

完成時間大約為12 小時

建議:4 weeks of study, 2-5 hours/week...
可選語言

英語(English)

字幕:英語(English)...

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 8 小時

Simple Introduction to Machine Learning

The focus of this module is to introduce the concepts of machine learning with as little mathematics as possible. We will introduce basic concepts in machine learning, including logistic regression, a simple but widely employed machine learning (ML) method. Also covered is multilayered perceptron (MLP), a fundamental neural network. The concept of deep learning is discussed, and also related to simpler models. ...
Reading
23 個視頻(共 164 分鐘), 1 個閱讀材料, 14 個測驗
Video23 個視頻
What Is Machine Learning?5分鐘
Logistic Regression9分鐘
Interpretation of Logistic Regression9分鐘
Motivation for Multilayer Perceptron4分鐘
Multilayer Perceptron Concepts5分鐘
Multilayer Perceptron Math Model6分鐘
Deep Learning6分鐘
Example: Document Analysis3分鐘
Interpretation of Multilayer Perceptron9分鐘
Transfer Learning5分鐘
Model Selection7分鐘
Early History of Neural Networks14分鐘
Hierarchical Structure of Images6分鐘
Convolution Filters9分鐘
Convolutional Neural Network3分鐘
CNN Math Model6分鐘
How the Model Learns8分鐘
Advantages of Hierarchical Features4分鐘
CNN on Real Images9分鐘
Applications in Use and Practice10分鐘
Deep Learning and Transfer Learning7分鐘
Introduction to TensorFlow3分鐘
Reading1 個閱讀材料
Math for Data Science10分鐘
Quiz10 個練習
Intro to Machine Learning8分鐘
Logistic Regression8分鐘
Multilayer Perceptron8分鐘
Deep Learning8分鐘
Model Selection8分鐘
History of Neural Networks8分鐘
CNN Concepts10分鐘
CNN Math Model4分鐘
Applications In Use and Practice分鐘
Week 1 Comprehensive分鐘
2
完成時間(小時)
完成時間為 3 小時

Basics of Model Learning

In this module we will be discussing the mathematical basis of learning deep networks. We’ll first work through how we define the issue of learning deep networks as a minimization problem of a mathematical function. After defining our mathematical goal, we will introduce validation methods to estimate real-world performance of the learned deep networks. We will then discuss how gradient descent, a classical technique in optimization, can be used to achieve this mathematical goal. Finally, we will discuss both why and how stochastic gradient descent is used in practice to learn deep networks....
Reading
6 個視頻(共 44 分鐘), 5 個測驗
Video6 個視頻
How Do We Evaluate Our Networks?12分鐘
How Do We Learn Our Network?7分鐘
How Do We Handle Big Data?10分鐘
Early Stopping2分鐘
Model Learning with TensorFlow分鐘
Quiz3 個練習
Lesson One10分鐘
Lesson 210分鐘
Week 2 Comprehensive分鐘
3
完成時間(小時)
完成時間為 3 小時

Image Analysis with Convolutional Neural Networks

This week will cover model training, as well as transfer learning and fine-tuning. In addition to learning the fundamentals of a CNN and how it is applied, careful discussion is provided on the intuition of the CNN, with the goal of providing a conceptual understanding....
Reading
8 個視頻(共 45 分鐘), 6 個測驗
Video8 個視頻
Breakdown of the Convolution (1D and 2D)8分鐘
Core Components of the Convolutional Layer7分鐘
Activation Functions4分鐘
Pooling and Fully Connected Layers4分鐘
Training the Network6分鐘
Transfer Learning and Fine-Tuning4分鐘
CNN with TensorFlow分鐘
Quiz4 個練習
Lesson One10分鐘
Lesson 210分鐘
Lesson 36分鐘
Week 3 Comprehensive分鐘
4
完成時間(小時)
完成時間為 11 小時

Introduction to Natural Language Processing

This week will cover the application of neural networks to natural language processing (NLP), from simple neural models to the more complex. The fundamental concept of word embeddings is discussed, as well as how such methods are employed within model learning and usage for several NLP applications. A wide range of neural NLP models are also discussed, including recurrent neural networks, and specifically long short-term memory (LSTM) models....
Reading
13 個視頻(共 136 分鐘), 5 個測驗
Video13 個視頻
Words to Vectors7分鐘
Example of Word Embeddings11分鐘
Neural Model of Text14分鐘
The Softmax Function7分鐘
Methods for Learning Model Parameters9分鐘
More Details on How to Learn Model Parameters6分鐘
The Recurrent Neural Network11分鐘
Long Short-Term Memory20分鐘
Long Short-Term Memory Review11分鐘
Use of LSTM for Text Synthesis9分鐘
Simple and Effective Alternative Methods for Neural NLP15分鐘
Natural Language Processing with TensorFlow分鐘
Quiz4 個練習
Lesson 12分鐘
Lesson 22分鐘
Lesson 32分鐘
Week 4 Comprehensive30分鐘

講師

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Lawrence Carin

James L. Meriam Professor of Electrical and Computer Engineering
Electrical and Computer Engineering

關於 Duke University

Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world....

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