课程信息

6,305 次近期查看
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为11 小时
中文(繁体)
字幕:中文(繁体)
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为11 小时
中文(繁体)
字幕:中文(繁体)

提供方

国立台湾大学 徽标

国立台湾大学

教学大纲 - 您将从这门课程中学到什么

1

1

完成时间为 1 小时

Concept learning

完成时间为 1 小时
6 个视频 (总计 73 分钟), 2 个阅读材料, 1 个测验
6 个视频
1-2 Hypotheses ,Relation between Instance Space and Hypotheses14分钟
1-3 The Find-S Algorithm10分钟
1-4 Version Space and The List-Then Eliminate Algorithm12分钟
1-5 The Candidate Elimination Algorithm15分钟
1-6 Biased and Unbiased Hypothesis Space, Futility of Bias-Free Learning12分钟
2 个阅读材料
NTU MOOC 課程問題詢問與回報機制1分钟
課程投影片開放下載公告2分钟
1 个练习
Week 1 Quiz10分钟
2

2

完成时间为 2 小时

Computational Learning Theory

完成时间为 2 小时
8 个视频 (总计 120 分钟)
8 个视频
2-2 Setting 3, PAC Learnable10分钟
2-3 Exhausting the Version Space: Definition, Theorem ,Proof and some examples19分钟
2-4 Shatter, Dichotomy, VC dimension14分钟
2-5 Some examples and discussion about VC dimension14分钟
2-6 Upper and Lower Bounds on Sample Complexity with VC dimension, The Mistake Bound for Algorithms14分钟
2-7 Optimal Mistake Bound13分钟
2-8 The Weighted-Majority Algorithm and its Bound11分钟
1 个练习
Week 2 Quiz16分钟
3

3

完成时间为 2 小时

Classification

完成时间为 2 小时
6 个视频 (总计 114 分钟)
6 个视频
3-2 Learning Decision Tree, Information19分钟
3-3 Generalization and Overfitting, Kai Square Pruning,Rule Post-Pruning22分钟
3-4 Model Evaluation: Metrics for Performance Evaluation, Methods for Model Comparison19分钟
3-5 Ensemble: Embedding, Bagging and Boosting13分钟
3-6 Support Vector Machine: Optimization, Soft Margins, and Kernel Trick21分钟
1 个练习
Week 3 Quiz24分钟
4

4

完成时间为 3 小时

Neural Network and Deep learning

完成时间为 3 小时
9 个视频 (总计 151 分钟)
9 个视频
4-2 Single-Layer Network and Perceptron Learning Rule15分钟
4-3 Multi-Layer Perceptron, Back Propagation Learning, Decline of ANN10分钟
4-4 Cascade Correlation Neural Networks, Deep or Shallow Structure23分钟
4-5 Deep Learning: Convolutional Neural Networks17分钟
4-6 LeNet 5, Dropout, ReLU and the Variants, Maxout, Residual Net18分钟
4-7 Recurrent Networks, Long Short-Term Memory (LSTM), Neural Turing Machine, Memory-Augmented Neural Networks (MANN)15分钟
4-8 Autoencoder: Denoising Autoencoder, Stacked Autoencoder and Variational Autoencoder12分钟
4-9 Generative Adversarial Net (GAN), AE+GAN and Its Applications16分钟
1 个练习
Week 4 Quiz16分钟

审阅

来自人工智慧:機器學習與理論基礎 (ARTIFICIAL INTELLIGENCE - LEARNING & THEORY)的热门评论

查看所有评论

常见问题

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

还有其他问题吗?请访问 学生帮助中心