- Building Machine Learning Systems with Python
- Willi Richert Luis Pedro Coelho
- 122字
- 2021-08-13 16:35:47
Summary
That was a tough ride, from preprocessing over clustering to a solution that can convert noisy text into a meaningful concise vector representation that we can cluster. If we look at the efforts we had to do to finally be able to cluster, it was more than half of the overall task, but on the way, we learned quite a bit on text processing and how simple counting can get you very far in the noisy real-world data.
The ride has been made much smoother though, because of Scikit and its powerful packages. And there is more to explore. In this chapter we were scratching the surface of its capabilities. In the next chapters we will see more of its powers.
推薦閱讀
- C語言程序設計實踐教程(第2版)
- Modular Programming with Python
- Getting Started with ResearchKit
- x86匯編語言:從實模式到保護模式(第2版)
- Learning Laravel 4 Application Development
- Java程序設計與實踐教程(第2版)
- Visual C++數字圖像處理技術詳解
- Windows Forensics Cookbook
- ArcGIS By Example
- MySQL從入門到精通(軟件開發視頻大講堂)
- Frank Kane's Taming Big Data with Apache Spark and Python
- Regression Analysis with Python
- Emotional Intelligence for IT Professionals
- scikit-learn Cookbook(Second Edition)
- MongoDB Cookbook