Boosting: AdaBoost and Gradient Boosting
Bagging builds trees to cut variance. builds them to cut bias: each new tree focuses on what the ensemble got wrong so far. This chapter develops boosting from AdaBoost (reweight the mistakes) to the more general and pow
阅读文章 →Modern Gradient Boosting: XGBoost, LightGBM, CatBoost
Friedman's gradient boosting is the idea; , , and are the engineering that made it dominate. Each adds algorithmic and systems innovations — regularized objectives, second-order optimization, histogram binning, clever tr
阅读文章 →Feature Importance and Interpretability
A single tree is a readable flowchart, but a forest of hundreds or a thousand boosted trees is a black box. The good news: tree ensembles support some of the best interpretability tools in machine learning. This chapter
阅读文章 →Practical Tree Modeling
Knowing the algorithms is half the battle; the other half is the craft of applying them to messy real data. This chapter is a practitioner's checklist: handling categoricals and missing values, dealing with class imbalan
阅读文章 →Specialized and Advanced Trees
Beyond classification, regression, forests, and boosting lies a rich ecosystem of tree variants tuned for special jobs: detecting anomalies, ranking search results, modeling time-to-event, quantifying uncertainty, and sq
阅读文章 →Trees versus the World: When to Use What
When should you reach for a tree ensemble, and when for something else? This chapter places trees in the broader modeling landscape — against linear models and against deep learning — and explains the that make trees so
阅读文章 →Tree-Based Methods in Machine Learning, Deep Learning, and AI
This capstone gathers the threads. Tree-based methods are not a quaint pre-deep-learning relic — they are a living, dominant branch of modern AI, and increasingly they with deep learning. We tour their reign over tabular
阅读文章 →Preface: how to use this book
There is a quiet truth in applied machine learning: while deep networks dominate images, audio, and text, the workhorse for the that run businesses — spreadsheets of customers, transactions, sensors, and records — is a f
阅读文章 →Playwright Tutorial: Website Testing and Data Crawling
This directory contains comprehensive examples for using Playwright with Python for both website testing and data crawling.
阅读文章 →Quick Start Guide
Get started with web scraping in 5 minutes
阅读文章 →Web Crawling Tutorial: From Beginner to Advanced
This repository contains comprehensive teaching materials and Python code examples for learning web crawling at three different levels.
阅读文章 →Scrapy Example
This directory contains a Scrapy spider example.
阅读文章 →Advanced Level: Professional Web Scraping
By the end of this level, you will be able to: Use Selenium to scrape JavaScriptheavy websites Implement asynchronous scraping for better performance Use the Scrapy framework for largescale scraping Integrate scrapers wi
阅读文章 →Advanced Level Exercises
Hint: Try scraping a modern SPA Single Page Application website.
阅读文章 →Beginner Level: Introduction to Web Scraping
By the end of this level, you will be able to: Understand what web scraping is and when to use it Make HTTP requests to fetch web pages Parse HTML content using BeautifulSoup Extract specific data from web pages Handle b
阅读文章 →Beginner Level Exercises
Hint: Try scraping from a news website like BBC News or CNN.
阅读文章 →Intermediate Level: Advanced Web Scraping Techniques
By the end of this level, you will be able to: Handle pagination and navigate through multiple pages Submit forms and handle POST requests Implement rate limiting and respectful scraping Handle errors gracefully with ret
阅读文章 →Intermediate Level Exercises
Hint: Try scraping from a demo ecommerce site or use quotes.toscrape.com for practice.
阅读文章 →