课程信息
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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

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中级

完成时间大约为12 小时

建议:11 hours/week...

英语(English)

字幕:英语(English)

您将获得的技能

Statistical AnalysisMachine LearningPython ProgrammingComputer ProgrammingLinear Algebra

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12 小时

建议:11 hours/week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 2 小时

What Does Good Data look like?

11 个视频 (总计 65 分钟), 2 个阅读材料, 3 个测验
11 个视频
Business Understanding and Problem Discovery9分钟
No Free Lunch Theorem5分钟
Exploring the process of problem definition7分钟
Data Acquisition and Understanding8分钟
Metadata Matters5分钟
Dealing with Multimodal Data2分钟
Features and transformations of raw data6分钟
Identifying Data from Problem5分钟
Case Study: Problem from Data6分钟
Weekly Summary What does good data look like?4分钟
2 个阅读材料
Machine Learning Process Lifecycle Review10分钟
Match Data to the needs of the learning Algorithm10分钟
3 个练习
Business Understanding and Problem Discovery (BUPD) Review10分钟
Data Acquisition and Understanding Review10分钟
Module 1 Quiz30分钟
2
完成时间为 2 小时

Preparing your Data for Machine Learning Success

11 个视频 (总计 61 分钟), 4 个测验
11 个视频
Converting to Useful Forms7分钟
Data Quality5分钟
How Much Data Do I Need?4分钟
Everything has to be Numbers6分钟
Types of Data5分钟
Aligning Similar Data4分钟
Imputing Missing Values7分钟
Data Transformations7分钟
Weekly Summary: Preparing your Data for Machine Learning Success1分钟
Data Cleaning: Everybody's favourite task4分钟
4 个练习
Data Warehousing Review10分钟
Everything has to be Numbers Review10分钟
Types of Data Review10分钟
Module 2 Quiz30分钟
3
完成时间为 5 小时

Feature Engineering for MORE Fun & Profit

8 个视频 (总计 45 分钟), 2 个阅读材料, 4 个测验
8 个视频
Useful/Useless Features6分钟
How Many Features?5分钟
What is Unsupervised Learning6分钟
Feature Selection7分钟
Feature Extraction2分钟
Transfer Learning7分钟
Weekly Summary: Feature Engineering for MORE Fun & Profit1分钟
2 个阅读材料
Possibilities for Text Features10分钟
Word Embeddings10分钟
3 个练习
Understanding Features6分钟
Building Good Features6分钟
Understanding Transfer Learning4分钟
4
完成时间为 2 小时

Bad Data

9 个视频 (总计 48 分钟), 4 个测验
9 个视频
Generalization and how machines actually learn6分钟
Bias in Data Sources3分钟
Bias and variance tradeoff6分钟
Outliers5分钟
Skewed Distributions7分钟
Badness Multipliers4分钟
Live Data Danger6分钟
Weekly Summary: Bad Data1分钟
4 个练习
Mistakes Computers Make10分钟
Data: Skewed Distributions10分钟
Live Data Dangers10分钟
Module 4 Quiz30分钟

讲师

Avatar

Anna Koop

Senior Scientific Advisor
Alberta Machine Intelligence Institute, University of Alberta

关于 Alberta Machine Intelligence Institute

The Alberta Machine Intelligence Institute (Amii) is home to some of the world’s top talent in machine intelligence. We’re an Alberta-based research institute that pushes the bounds of academic knowledge and guides business understanding of artificial intelligence and machine learning....

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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