10最好的自然语言处理教程推荐

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特写 iPhone，显示 Udemy 应用程序和带笔记本的笔记本电脑有数以千计的在线课程和课程可以帮助您提高 自然语言处理 技能并获得 自然语言处理 证书。

在这篇博客文章中，我们的专家汇总了 10 个精选列表 最好的 自然语言处理 课程, 现在在线提供的教程、培训计划、课程和认证。

我们只包括那些符合我们高质量标准的课程。我们花了很多时间和精力来为您收集这些。这些课程适合所有级别的初学者、中级学习者和专家。

以下是这些课程以及它们为您提供的内容！

10最好的自然语言处理教程推荐

课程名 在校生（人数） 评论（计数）
1. NLP – Natural Language Processing with Python 我们的最佳选择 59350+ 11609+
2. Modern Natural Language Processing in Python 47276+ 1452+
3. Data Science: Natural Language Processing (NLP) in Python 42317+ 11067+
4. Natural Language Processing with Deep Learning in Python 41651+ 6997+
5. Natural Language Processing: NLP With Transformers in Python 17471+ 867+
6. U&P AI – Natural Language Processing (NLP) with Python 13868+ 1144+
7. Introduction to Natural Language Processing (NLP) 13254+ 3480+
8. “From 0 to 1: Machine Learning, NLP & Python-Cut to the Chase” 8715+ 898+
9. Hands On Natural Language Processing (NLP) using Python 8561+ 1440+
10. Machine Learning: Natural Language Processing in Python (V2) 5424+ 1154+

1. NLP – Natural Language Processing with Python 经过 Jose Portilla Udemy课程 我们的最佳选择

“Learn to use Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing”

截至目前，超过 59350+ 人们已经注册了这门课程，而且已经结束了 11609+ 评论.

课程内容
Introduction
Python Text Basics
Natural Language Processing Basics
Part of Speech Tagging and Named Entity Recognition
Text Classification
Semantics and Sentiment Analysis
Topic Modeling
Deep Learning for NLP
BONUS SECTION: THANK YOU!

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2. Modern Natural Language Processing in Python 经过 “Martin Jocqueviel, Ligency I Team, Ligency Team” Udemy课程

Solve Seq2Seq and Classification NLP tasks with Transformer and CNN using Tensorflow 2 in Google Colab

截至目前，超过 47276+ 人们已经注册了这门课程，而且已经结束了 1452+ 评论.

课程内容
Introduction
CNN for NLP – Intuition
CNN for NLP – Application (sentimental analysis)
Transformer – Intuition
Transformer – Application

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3. Data Science: Natural Language Processing (NLP) in Python 经过 Lazy Programmer Inc. Udemy课程

“Applications: decrypting ciphers, spam detection, sentiment analysis, article spinners, and latent semantic analysis.”

截至目前，超过 42317+ 人们已经注册了这门课程，而且已经结束了 11067+ 评论.

课程内容
Natural Language Processing – What is it used for?
Course Preparation
Machine Learning Basics Review
Markov Models
Decrypting Ciphers
Build your own spam detector
Build your own sentiment analyzer
NLTK Exploration
Latent Semantic Analysis
Write your own article spinner
How to learn more about NLP
Setting Up Your Environment (FAQ by Student Request)
Extra Help With Python Coding for Beginners (FAQ by Student Request)
Effective Learning Strategies for Machine Learning (FAQ by Student Request)
Appendix / FAQ Finale

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4. Natural Language Processing with Deep Learning in Python 经过 “Lazy Programmer Team, Lazy Programmer Inc.” Udemy课程

“Complete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets”

截至目前，超过 41651+ 人们已经注册了这门课程，而且已经结束了 6997+ 评论.

课程内容
“Outline, Review, and Logistical Things
Beginner’s Corner: Working with Word Vectors
Review of Language Modeling and Neural Networks
Word Embeddings and Word2Vec
Word Embeddings using GloVe
Unifying Word2Vec and GloVe
Using Neural Networks to Solve NLP Problems
Recursive Neural Networks (Tree Neural Networks)
Theano and Tensorflow Basics Review
Setting Up Your Environment (FAQ by Student Request)
Extra Help With Python Coding for Beginners (FAQ by Student Request)
Effective Learning Strategies for Machine Learning (FAQ by Student Request)
Appendix / FAQ Finale”

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5. Natural Language Processing: NLP With Transformers in Python 经过 James Briggs Udemy课程

“Learn next-generation NLP with transformers for sentiment analysis, Q&A, similarity search, NER, and more”

截至目前，超过 17471+ 人们已经注册了这门课程，而且已经结束了 867+ 评论.

课程内容
Introduction
NLP and Transformers
Preprocessing for NLP
Attention
Language Classification
[Project] Sentiment Model With TensorFlow and Transformers
Long Text Classification With BERT
Named Entity Recognition (NER)
Question and Answering
Metrics For Language
Reader-Retriever QA With Haystack
[Project] Open-Domain QA
Similarity
Pre-Training Transformer Models

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6. U&P AI – Natural Language Processing (NLP) with Python 经过 Abdulhadi Darwish Udemy课程

“Become an NLP Engineer by creating real projects using Python, semantic search, text mining and search engines!”

截至目前，超过 13868+ 人们已经注册了这门课程，而且已经结束了 1144+ 评论.

课程内容
Getting an Idea of NLP and its Applications
Feature Engineering
Dealing with corpus and WordNet
Create your Vocabulary for any NLP Model
Word2Vec in Detail and what is going on under the hood
Find and Represent the Meaning or Topic of Natural Language Text

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7. Introduction to Natural Language Processing (NLP) 经过 Brian Sacash Udemy课程

Learn how to analyze text data.

截至目前，超过 13254+ 人们已经注册了这门课程，而且已经结束了 3480+ 评论.

课程内容
“Course Introduction
Setup
Python Refresher
NLTK and the Basics
Tokenization , Tagging, Chunking
Custom Sources
Projects
Appendix”

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8. “From 0 to 1: Machine Learning, NLP & Python-Cut to the Chase” 经过 Loony Corn Udemy课程

“A down-to-earth, shy but confident take on machine learning techniques that you can put to work today”

截至目前，超过 8715+ 人们已经注册了这门课程，而且已经结束了 898+ 评论.

课程内容
Introduction
Jump right in : Machine learning for Spam detection
Solving Classification Problems
Clustering as a form of Unsupervised learning
Association Detection
Dimensionality Reduction
Regression as a form of supervised learning
Natural Language Processing and Python
Sentiment Analysis
Decision Trees
A Few Useful Things to Know About Overfitting
Random Forests
Recommendation Systems
Recommendation Systems in Python
A Taste of Deep Learning and Computer Vision
Quizzes

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9. Hands On Natural Language Processing (NLP) using Python 经过 Next Edge Coding Udemy课程

“Learn Natural Language Processing ( NLP ) & Text Mining by creating text classifier, article summarizer, and many more.”

截至目前，超过 8561+ 人们已经注册了这门课程，而且已经结束了 1440+ 评论.

课程内容
Introduction to the Course
Getting the required softwares
Python Crash Course
Regular Expressions
Numpy and Pandas
NLP Core
Project 1 – Text Classification
Project 2 – Twitter Sentiment Analysis
Project 3 – Text Summarization
Word2Vec Analysis
Conclusion

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10. Machine Learning: Natural Language Processing in Python (V2) 经过 “Lazy Programmer Inc., Lazy Programmer Team” Udemy课程

“NLP: Use Markov Models, NLTK, Artificial Intelligence, Deep Learning, Machine Learning, and Data Science in Python”

截至目前，超过 5424+ 人们已经注册了这门课程，而且已经结束了 1154+ 评论.

课程内容
Introduction
Getting Set Up
Vector Models and Text Preprocessing
Probabilistic Models (Introduction)
Markov Models (Intermediate)
Article Spinner (Intermediate)
Cipher Decryption (Advanced)
Machine Learning Models (Introduction)
Spam Detection
Sentiment Analysis
Text Summarization
Topic Modeling
Latent Semantic Analysis (Latent Semantic Indexing)
Deep Learning (Introduction)
The Neuron
Feedforward Artificial Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
Setting Up Your Environment FAQ
Extra Help With Python Coding for Beginners FAQ
Effective Learning Strategies for Machine Learning FAQ
Appendix / FAQ Finale

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下面是一些关于学习的常见问题自然语言处理

学习自然语言处理需要多长时间？

“学习自然语言处理需要多长时间”这个问题的答案是。 . .这取决于。每个人都有不同的需求，每个人都在不同的场景下工作，所以一个人的答案可能与另一个人的答案完全不同。

考虑这些问题：你想学习 自然语言处理 是为了什么？你的出发点在哪里？您是初学者还是有使用 自然语言处理 的经验？你能练习多少？每天1小时？每周40小时？ 查看本课程关于 自然语言处理.

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在哪里学习 自然语言处理？

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