Machine Learning

Introduction 介绍 Welcome to Kaggle’s Intermediate Machine Learning course! 欢迎来到 Kaggle 的 中级机器学习 课程！ If you have some background in machine learning and you’d like to learn how to quickly improve the quality of your models, you’re in the right place! In this course, you will accelerate your machine learning expertise by learning how to: […]

This notebook is an exercise in the Introduction to Machine Learning course. You can reference the tutorial at this link. Introduction 介绍 In this exercise, you will create and submit predictions for a Kaggle competition. You can then improve your model (e.g. by adding features) to improve and see how you stack up to others […]

Machine learning competitions are a great way to improve your data science skills and measure your progress. 机器学习竞赛是提高数据科学技能和衡量进步的好方法。 Your Turn 到你了 Use what you’ve learned in the course to create a submission to a Kaggle competition! 使用您在课程中学到的知识创建提交到 Kaggle 竞赛！ In the next exercise, you will create and submit predictions for the House Prices Competition for […]

Machine learning competitions are a great way to improve your data science skills and measure your progress. 机器学习竞赛是提高数据科学技能和衡量进步的好方法。 Your Turn 到你了 Use what you’ve learned in the course to create a submission to a Kaggle competition! 使用您在课程中学到的知识创建提交到 Kaggle 竞赛！ In the next exercise, you will create and submit predictions for the House Prices Competition for […]

Machine learning competitions are a great way to improve your data science skills and measure your progress. 机器学习竞赛是提高数据科学技能和衡量进步的好方法。 Your Turn 到你了 Use what you’ve learned in the course to create a submission to a Kaggle competition! 使用您在课程中学到的知识创建提交到 Kaggle 竞赛！ In the next exercise, you will create and submit predictions for the House Prices Competition for […]

This notebook is an exercise in the Introduction to Machine Learning course. You can reference the tutorial at this link. Recap 回顾 Here’s the code you’ve written so far. 这是您到目前为止编写的代码。 # Code you have previously used to load data import pandas as pd from sklearn.metrics import mean_absolute_error from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeRegressor […]

Introduction 介绍 Decision trees leave you with a difficult decision. A deep tree with lots of leaves will overfit because each prediction is coming from historical data from only the few houses at its leaf. But a shallow tree with few leaves will perform poorly because it fails to capture as many distinctions in the […]