python3中情感分类
This post is the last of the three sequential posts on steps to build a sentiment classifier. Having done some exploratory text analysis and preprocessed the text, it’s time to classify reviews to sentiments. In this post, we will first look at 2 ways to get sentiments without building a model then build a custom model.
这篇文章是关于建立情感分类器的三个连续文章中的最后一篇。 经过一些探索性的文本分析并预处理了文本 ，是时候对评论进行分类了。 在本文中，我们将首先探讨两种无需构建模型即可获得情感的方法，然后构建自定义模型。
Before we dive in, let’s take a step back and look at the bigger picture really quickly. CRISP-DM methodology outlines the process flow for a successful data science project. In this post, we will do some of the tasks that a data scientist would go through during the modelling stage.
在我们深入之前，让我们退后一步，真正快速地了解大局。 CRISP-DM方法论概述了成功的数据科学项目的流程。 在本文中，我们将完成数据科学家在建模阶段要完成的一些任务。
0. Python设置 (0. Python setup)
This post assumes that the reader (
