This course will help us to evaluate and compare the models we have developed in previous courses. So far we have developed techniques for regression and classification, but how low should the error of a classifier be (for example) before we decide that the classifier is "good enough"? Or how do we decide which of two regression algorithms is better?
课程信息
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第 3 门课程（共 4 门）
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中级
完成时间大约为8 小时
英语（English）
字幕：英语（English）
您将学到的内容有
Understand the definitions of simple error measures (e.g. MSE, accuracy, precision/recall).
Evaluate the performance of regressors / classifiers using the above measures.
Understand the difference between training/testing performance, and generalizability.
Understand techniques to avoid overfitting and achieve good generalization performance.
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。
第 3 门课程（共 4 门）
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8 小时
英语（English）
字幕：英语（English）
提供方
加州大学圣地亚哥分校
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
教学大纲 - 您将从这门课程中学到什么
完成时间为 3 小时
Week 1: Diagnostics for Data
For this first week, we will go over the syllabus, download all course materials, and get your system up and running for the course. We will also introduce the basics of diagnostics for the results of supervised learning.
完成时间为 3 小时
6 个视频 （总计 49 分钟）, 4 个阅读材料, 3 个测验
6 个视频
Motivation Behind the MSE8分钟
Regression Diagnostics: MSE and R²6分钟
Over- and Under-Fitting6分钟
Classification Diagnostics: Accuracy and Error11分钟
Classification Diagnostics: Precision and Recall12分钟
4 个阅读材料
Syllabus10分钟
Setting Up Your System10分钟
(Optional) Additional Resources and Recommended Readings10分钟
Course Materials10分钟
3 个练习
Review: Regression Diagnostics30分钟
Review: Classification Diagnostics30分钟
Diagnostics for Data30分钟
完成时间为 2 小时
Week 2: Codebases, Regularization, and Evaluating a Model
This week, we will learn how to create a simple bag of words for analysis. We will also cover regularization and why it matters when building a model. Lastly, we will evaluate a model with regularization, focusing on classifiers.
完成时间为 2 小时
4 个视频 （总计 35 分钟）
4 个视频
Model Complexity and Regularization10分钟
Adding a Regularizer to our Model, and Evaluating the Regularized Model8分钟
Evaluating Classifiers for Ranking4分钟
4 个练习
Review: Setting Up a Codebase30分钟
Review: Regularization5分钟
Review: Evaluating a Model5分钟
Codebases, Regularization, and Evaluating a Model45分钟
完成时间为 2 小时
Week 3: Validation and Pipelines
This week, we will learn about validation and how to implement it in tandem with training and testing. We will also cover how to implement a regularization pipeline in Python and introduce a few guidelines for best practices.
完成时间为 2 小时
4 个视频 （总计 24 分钟）
4 个视频
Validation5分钟
“Theorems” About Training, Testing, and Validation8分钟
Implementing a Regularization Pipeline in Python5分钟
Guidelines on the Implementation of Predictive Pipelines5分钟
3 个练习
Review: Validation30分钟
Review: Predictive Pipelines30分钟
Predictive Pipelines20分钟
完成时间为 1 小时
Final Project
In the final week of this course, you will continue building on the project from the first and second courses of Python Data Products for Predictive Analytics with simple predictive machine learning algorithms. Find a dataset, clean it, and perform basic analyses on the data. Evaluate your model, validate your analyses, and make sure you aren't overfitting the data.
完成时间为 1 小时
2 个阅读材料
2 个阅读材料
Project Description10分钟
Where to Find Datasets10分钟
关于 Python Data Products for Predictive Analytics 专项课程
Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego.
常见问题
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您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
Is financial aid available?
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
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