课程信息

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完成时间大约为9 小时
英语(English)
字幕:英语(English)
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。
完成时间大约为9 小时
英语(English)
字幕:英语(English)

提供方

Alberta Machine Intelligence Institute 徽标

Alberta Machine Intelligence Institute

教学大纲 - 您将从这门课程中学到什么

1

1

完成时间为 4 小时

Classification using Decision Trees and k-NN

完成时间为 4 小时
8 个视频 (总计 46 分钟), 4 个阅读材料, 2 个测验
8 个视频
What does a classifier actually do?5分钟
Classification in scikit-learn3分钟
What are decision trees?6分钟
Generalization and overfitting8分钟
Classification using k-nearest neighbours8分钟
Distance measures8分钟
Weekly summary2分钟
4 个阅读材料
Math Review10分钟
Scikitlearn documentation for decision trees (Optional)10分钟
Scikitlearn documentation for random forests (Optional)10分钟
Scikitlearn documentation for k-nearest neighbours (Optional)10分钟
2 个练习
Supervised Learning Basics
Understanding Classification with Decision Trees and k-NN20分钟
2

2

完成时间为 2 小时

Functions for Fun and Profit

完成时间为 2 小时
9 个视频 (总计 62 分钟), 1 个阅读材料, 4 个测验
9 个视频
Optimal line-fitting8分钟
Loss and Convexity7分钟
Gradient Descent9分钟
Nonlinear features and model complexity6分钟
Bias and variance tradeoff6分钟
Regularizers5分钟
Loss for Classification7分钟
Weekly summary4分钟
1 个阅读材料
Scikitlearn documentation for linear regression (Optional)10分钟
4 个练习
Regression Basics
Understanding Model Complexity
From Regression to Classification2分钟
The Regression side of Supervised Learning20分钟
3

3

完成时间为 3 小时

Regression for Classification: Support Vector Machines

完成时间为 3 小时
6 个视频 (总计 34 分钟), 1 个阅读材料, 2 个测验
6 个视频
Neural Networks9分钟
Hinge Loss6分钟
Basics of Support Vector Machines6分钟
Kernels6分钟
Weekly Summary1分钟
1 个阅读材料
Scikitlearn documentation for SVMs (Optional)10分钟
2 个练习
Understanding Support Vector Machines
Regression-based Classification10分钟
4

4

完成时间为 1 小时

Contrasting Models

完成时间为 1 小时
8 个视频 (总计 46 分钟), 1 个阅读材料, 1 个测验
8 个视频
Classification assessment6分钟
Learning Curves6分钟
Testing your models7分钟
Cross validation5分钟
Parameter tuning and grid search5分钟
Model Parameters6分钟
Weekly Summary1分钟
1 个阅读材料
Some resources on model assessment (Optional)10分钟
1 个练习
Contrasting Models

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关于 Machine Learning: Algorithms in the Real World 专项课程

This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application. After completing all four courses, you will have gone through the entire process of building a machine learning project. You will be able to clearly define a machine learning problem, identify appropriate data, train a classification algorithm, improve your results, and deploy it in the real world. You will also be able to anticipate and mitigate common pitfalls in applied machine learning....
Machine Learning: Algorithms in the Real World

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