跳至内容
首页Python

课程

Natural Language Processing (NLP) in Python

中级技能水平
更新时间 2025年7月
Master text analysis with essential NLP techniques from preprocessing to advanced transformer models.
免费开始课程
PythonArtificial Intelligence4 小时13 视频42 练习3,550 经验值6,890成就声明

创建您的免费帐户

继续操作即表示您接受我们的《使用条款》和《隐私政策》,并同意您的数据存储在美国。

深受数千家公司学习者的喜爱

Group

培训2人或更多?

试用DataCamp for Business

课程描述

Build a Strong NLP Foundation

Unlock the power of Natural Language Processing (NLP) and take your text analysis skills to the next level! This course equips you with essential tools to process, analyze, and extract insights from text data. Start with the fundamentals of text processing, from tokenization to cleaning and normalizing text by removing stop words, punctuation, and applying lemmatization and stemming to improve text consistency.

Extract Meaningful Features from Text

Go beyond raw text and transform it into numerical representations! Explore the Bag-of-Words representation, dive into TF-IDF vectorization, and leverage powerful word embeddings like Word2Vec and GloVe to capture semantic relationships between words.

Classify and Generate Text with AI

Harness the power of state-of-the-art transformer models using Hugging Face pipelines. Learn how to perform sentiment analysis, classify content, analyze question-answer relationships, assess grammatical acceptability, and generate text using various models. Explore Named Entity Recognition (NER), Part-of-Speech (PoS) tagging, text summarization, and translation to expand your NLP toolkit.

Master key NLP libraries

By the end of this course, you’ll have a strong grasp of NLP fundamentals and hands-on experience with key libraries such as nltk, sklearn, gensim, and Hugging Face’s transformers. Start your journey today and transform the way you interact with text data!

先决条件

Python Toolbox
1

Text Processing Fundamentals

Learn the essentials of text processing in Natural Language Processing (NLP). Master techniques such as tokenization, stop word and punctuation removal, and text normalization with lowercasing, stemming, and lemmatization to prepare text data for further analysis and insight extraction.
开始章节
2

Feature Extraction from Text

3

Text Classification with Hugging Face

4

Token Classification and Text Generation

Dive into the core of modern NLP applications with token classification and text generation techniques. Learn to extract meaningful entities and grammatical structures using NER and PoS tagging. Master both extractive and abstractive question answering, and explore advanced generation tasks including summarization, translation, and language modeling using Hugging Face pipelines.
开始章节
Natural Language Processing (NLP) in Python
课程完成

获得成就证明

将此证书添加到你的 LinkedIn 档案、简历或履历中
在社交媒体和绩效评估中分享
立即注册

加入超过19百万学习者,今天就开始Natural Language Processing (NLP) in Python!

创建您的免费帐户

继续操作即表示您接受我们的《使用条款》和《隐私政策》,并同意您的数据存储在美国。

通过 DataCamp for Mobile 提升您的数据技能

随时随地通过我们的移动课程和每日 5 分钟编程挑战提升技能。