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?
本课程是 Python Data Products for Predictive Analytics 专项课程 专项课程的一部分
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第 3 门课程（共 4 门）
中级
完成时间大约为9 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
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.
可灵活调整截止日期
根据您的日程表重置截止日期。
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）
中级
完成时间大约为9 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
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.
授课大纲 - 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
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）
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）
完成时间为 2 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 2 小时
2 个阅读材料
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.
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