[FreeCourseLab.com] Udemy - NLP - Natural Language Processing with Python

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[FreeCourseLab.com] Udemy - NLP - Natural Language Processing with Python

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文件大小： 4.81G
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收录时间：2022-02-02
最近下载：2025-07-22

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文件列表

  • 7. Topic Modeling/5. Latent Dirichlet Allocation with Python - Part Two.mp4 134.6 MB
  • 3. Natural Language Processing Basics/4. Spacy Basics.mp4 134.5 MB
  • 8. Deep Learning for NLP/15. Creating Chat Bots with Python - Part Four.mp4 131.6 MB
  • 2. Python Text Basics/3. Working with Text Files with Python - Part Two.mp4 124.2 MB
  • 8. Deep Learning for NLP/14. Creating Chat Bots with Python - Part Three.mp4 122.8 MB
  • 6. Semantics and Sentiment Analysis/3. Semantics and Word Vectors with Spacy.mp4 120.3 MB
  • 4. Part of Speech Tagging and Named Entity Recognition/2. Part of Speech Tagging.mp4 115.4 MB
  • 5. Text Classification/9. Text Feature Extraction - Code Along Implementations.mp4 113.4 MB
  • 3. Natural Language Processing Basics/10. Phrase Matching and Vocabulary - Part One.mp4 113.3 MB
  • 8. Deep Learning for NLP/8. Text Generation with LSTMs with Keras and Python - Part One.mp4 105.8 MB
  • 8. Deep Learning for NLP/10. Text Generation with LSTMS with Keras - Part Three.mp4 104.4 MB
  • 2. Python Text Basics/5. Regular Expressions Part One.vtt 99.8 MB
  • 2. Python Text Basics/5. Regular Expressions Part One.mp4 99.8 MB
  • 4. Part of Speech Tagging and Named Entity Recognition/7. Sentence Segmentation.mp4 98.3 MB
  • 8. Deep Learning for NLP/9. Text Generation with LSTMs with Keras and Python - Part Two.mp4 95.6 MB
  • 6. Semantics and Sentiment Analysis/5. Sentiment Analysis with NLTK.mp4 95.5 MB
  • 8. Deep Learning for NLP/4. Keras Basics - Part One.mp4 95.3 MB
  • 1. Introduction/1.1 UPDATED_NLP_COURSE.zip.zip 93.8 MB
  • 1. Introduction/5.1 UPDATED_NLP_COURSE.zip.zip 93.8 MB
  • 5. Text Classification/10. Text Feature Extraction - Code Along - Part Two.mp4 93.7 MB
  • 6. Semantics and Sentiment Analysis/8. Sentiment Analysis Project Assessment - Solutions.mp4 93.2 MB
  • 5. Text Classification/6. Scikit-Learn Primer - Code Along Part One.mp4 92.6 MB
  • 1. Introduction/4. Installation and Setup Lecture.mp4 92.4 MB
  • 7. Topic Modeling/7. Non-negative Matrix Factorization with Python.mp4 87.8 MB
  • 3. Natural Language Processing Basics/5. Tokenization - Part One.mp4 79.9 MB
  • 2. Python Text Basics/4. Working with PDFs.vtt 77.5 MB
  • 2. Python Text Basics/4. Working with PDFs.mp4 77.4 MB
  • 8. Deep Learning for NLP/13. Creating Chat Bots with Python - Part Two.mp4 76.9 MB
  • 4. Part of Speech Tagging and Named Entity Recognition/4. Named Entity Recognition - Part One.mp4 70.4 MB
  • 5. Text Classification/11. Text Classification Code Along Project.mp4 69.9 MB
  • 2. Python Text Basics/2. Working with Text Files with Python - Part One.mp4 68.3 MB
  • 4. Part of Speech Tagging and Named Entity Recognition/5. Named Entity Recognition - Part Two.mp4 66.3 MB
  • 5. Text Classification/3. Classification Metrics.mp4 64.9 MB
  • 2. Python Text Basics/6. Regular Expressions Part Two.mp4 64.1 MB
  • 2. Python Text Basics/6. Regular Expressions Part Two.vtt 64.1 MB
  • 4. Part of Speech Tagging and Named Entity Recognition/9. Part Of Speech Assessment - Solutions.mp4 64.0 MB
  • 7. Topic Modeling/3. Latent Dirichlet Allocation Overview.mp4 63.1 MB
  • 7. Topic Modeling/4. Latent Dirichlet Allocation with Python - Part One.mp4 62.8 MB
  • 3. Natural Language Processing Basics/13. NLP Basics Assessment Solution.mp4 60.7 MB
  • 7. Topic Modeling/9. Topic Modeling Project - Solutions.mp4 59.7 MB
  • 3. Natural Language Processing Basics/2. Spacy Setup and Overview.mp4 58.9 MB
  • 5. Text Classification/7. Scikit-Learn Primer - Code Along Part Two.mp4 58.7 MB
  • 5. Text Classification/4. Confusion Matrix.mp4 56.5 MB
  • 3. Natural Language Processing Basics/11. Phrase Matching and Vocabulary - Part Two.mp4 55.7 MB
  • 3. Natural Language Processing Basics/7. Stemming.mp4 54.4 MB
  • 4. Part of Speech Tagging and Named Entity Recognition/6. Visualizing Named Entity Recognition.mp4 54.2 MB
  • 8. Deep Learning for NLP/12. Creating Chat Bots with Python - Part One.mp4 53.7 MB
  • 5. Text Classification/2. Machine Learning Overview.vtt 53.2 MB
  • 5. Text Classification/2. Machine Learning Overview.mp4 53.2 MB
  • 2. Python Text Basics/8. Python Text Basics - Assessment Solutions.mp4 52.4 MB
  • 8. Deep Learning for NLP/7. LSTMs, GRU, and Text Generation.mp4 51.6 MB
  • 6. Semantics and Sentiment Analysis/6. Sentiment Analysis Code Along Movie Review Project.mp4 51.1 MB
  • 3. Natural Language Processing Basics/6. Tokenization - Part Two.mp4 48.1 MB
  • 3. Natural Language Processing Basics/8. Lemmatization.mp4 47.2 MB
  • 5. Text Classification/13. Text Classification Assessment Solutions.mp4 45.1 MB
  • 8. Deep Learning for NLP/11. Chat Bots Overview.mp4 44.0 MB
  • 7. Topic Modeling/6. Non-negative Matrix Factorization Overview.mp4 43.7 MB
  • 6. Semantics and Sentiment Analysis/2. Overview of Semantics and Word Vectors.mp4 42.2 MB
  • 3. Natural Language Processing Basics/9. Stop Words.mp4 39.1 MB
  • 8. Deep Learning for NLP/5. Keras Basics - Part Two.mp4 38.9 MB
  • 5. Text Classification/8. Text Feature Extraction Overview.mp4 36.6 MB
  • 8. Deep Learning for NLP/6. Recurrent Neural Network Overview.mp4 35.1 MB
  • 4. Part of Speech Tagging and Named Entity Recognition/3. Visualizing Part of Speech.mp4 34.4 MB
  • 5. Text Classification/12. Text Classification Assessment Overview.vtt 32.6 MB
  • 7. Topic Modeling/8. Topic Modeling Project - Overview.mp4 32.2 MB
  • 6. Semantics and Sentiment Analysis/4. Sentiment Analysis Overview.mp4 31.9 MB
  • 8. Deep Learning for NLP/3. Introduction to Neural Networks.mp4 30.9 MB
  • 3. Natural Language Processing Basics/12. NLP Basics Assessment Overview.mp4 26.9 MB
  • 6. Semantics and Sentiment Analysis/7. Sentiment Analysis Project Assessment.mp4 26.3 MB
  • 1. Introduction/1. Course Overview - DO NOT SKIP THIS LECTURE PLEASE. IMPORTANT INFO HERE!.mp4 24.3 MB
  • 8. Deep Learning for NLP/2. The Basic Perceptron Model.mp4 23.2 MB
  • 5. Text Classification/5. Scikit-Learn Primer - How to Use SciKit-Learn.mp4 22.4 MB
  • 5. Text Classification/5. Scikit-Learn Primer - How to Use SciKit-Learn.vtt 22.4 MB
  • 2. Python Text Basics/7. Python Text Basics - Assessment Overview.mp4 21.4 MB
  • 3. Natural Language Processing Basics/3. What is Natural Language Processing.mp4 20.0 MB
  • 4. Part of Speech Tagging and Named Entity Recognition/8. Part Of Speech Assessment.mp4 19.8 MB
  • 1. Introduction/3. Curriculum Overview.mp4 15.0 MB
  • 7. Topic Modeling/2. Overview of Topic Modeling.mp4 13.6 MB
  • 5. Text Classification/12. Text Classification Assessment Overview.mp4 9.7 MB
  • 5. Text Classification/11. Text Classification Code Along Project.vtt 9.7 MB
  • 8. Deep Learning for NLP/1. Introduction to Deep Learning for NLP.mp4 9.6 MB
  • 5. Text Classification/1. Introduction to Text Classification.mp4 5.7 MB
  • 7. Topic Modeling/1. Introduction to Topic Modeling Section.mp4 4.5 MB
  • 3. Natural Language Processing Basics/1. Introduction to Natural Language Processing.mp4 4.3 MB
  • 2. Python Text Basics/1. Introduction to Python Text Basics.mp4 3.9 MB
  • 4. Part of Speech Tagging and Named Entity Recognition/1. Introduction to Section on POS and NER.mp4 3.7 MB
  • 6. Semantics and Sentiment Analysis/1. Introduction to Semantics and Sentiment Analysis.mp4 2.3 MB
  • 2. Python Text Basics/3. Working with Text Files with Python - Part Two.vtt 25.1 kB
  • 3. Natural Language Processing Basics/4. Spacy Basics.vtt 23.8 kB
  • 8. Deep Learning for NLP/15. Creating Chat Bots with Python - Part Four.vtt 23.6 kB
  • 4. Part of Speech Tagging and Named Entity Recognition/2. Part of Speech Tagging.vtt 20.9 kB
  • 6. Semantics and Sentiment Analysis/3. Semantics and Word Vectors with Spacy.vtt 20.8 kB
  • 8. Deep Learning for NLP/14. Creating Chat Bots with Python - Part Three.vtt 20.4 kB
  • 8. Deep Learning for NLP/8. Text Generation with LSTMs with Keras and Python - Part One.vtt 20.2 kB
  • 5. Text Classification/6. Scikit-Learn Primer - Code Along Part One.vtt 19.5 kB
  • 3. Natural Language Processing Basics/10. Phrase Matching and Vocabulary - Part One.vtt 18.7 kB
  • 4. Part of Speech Tagging and Named Entity Recognition/7. Sentence Segmentation.vtt 18.7 kB
  • 7. Topic Modeling/5. Latent Dirichlet Allocation with Python - Part Two.vtt 18.2 kB
  • 5. Text Classification/9. Text Feature Extraction - Code Along Implementations.vtt 17.8 kB
  • 8. Deep Learning for NLP/4. Keras Basics - Part One.vtt 17.5 kB
  • 3. Natural Language Processing Basics/5. Tokenization - Part One.vtt 17.5 kB
  • 8. Deep Learning for NLP/10. Text Generation with LSTMS with Keras - Part Three.vtt 17.2 kB
  • 1. Introduction/4. Installation and Setup Lecture.vtt 17.0 kB
  • 8. Deep Learning for NLP/9. Text Generation with LSTMs with Keras and Python - Part Two.vtt 15.9 kB
  • 6. Semantics and Sentiment Analysis/5. Sentiment Analysis with NLTK.vtt 15.9 kB
  • 5. Text Classification/3. Classification Metrics.vtt 15.8 kB
  • 8. Deep Learning for NLP/13. Creating Chat Bots with Python - Part Two.vtt 14.8 kB
  • 2. Python Text Basics/2. Working with Text Files with Python - Part One.vtt 14.6 kB
  • 7. Topic Modeling/7. Non-negative Matrix Factorization with Python.vtt 14.2 kB
  • 8. Deep Learning for NLP/7. LSTMs, GRU, and Text Generation.vtt 13.8 kB
  • 7. Topic Modeling/3. Latent Dirichlet Allocation Overview.vtt 13.7 kB
  • 5. Text Classification/4. Confusion Matrix.vtt 13.6 kB
  • 6. Semantics and Sentiment Analysis/8. Sentiment Analysis Project Assessment - Solutions.vtt 13.5 kB
  • 8. Deep Learning for NLP/12. Creating Chat Bots with Python - Part One.vtt 13.2 kB
  • 5. Text Classification/10. Text Feature Extraction - Code Along - Part Two.vtt 13.0 kB
  • 7. Topic Modeling/4. Latent Dirichlet Allocation with Python - Part One.vtt 11.5 kB
  • 3. Natural Language Processing Basics/7. Stemming.vtt 11.3 kB
  • 4. Part of Speech Tagging and Named Entity Recognition/4. Named Entity Recognition - Part One.vtt 11.2 kB
  • 5. Text Classification/7. Scikit-Learn Primer - Code Along Part Two.vtt 10.7 kB
  • 4. Part of Speech Tagging and Named Entity Recognition/5. Named Entity Recognition - Part Two.vtt 10.4 kB
  • 3. Natural Language Processing Basics/2. Spacy Setup and Overview.vtt 10.4 kB
  • 8. Deep Learning for NLP/6. Recurrent Neural Network Overview.vtt 10.3 kB
  • 8. Deep Learning for NLP/11. Chat Bots Overview.vtt 10.0 kB
  • 6. Semantics and Sentiment Analysis/2. Overview of Semantics and Word Vectors.vtt 9.6 kB
  • 6. Semantics and Sentiment Analysis/6. Sentiment Analysis Code Along Movie Review Project.vtt 9.2 kB
  • 4. Part of Speech Tagging and Named Entity Recognition/6. Visualizing Named Entity Recognition.vtt 8.9 kB
  • 4. Part of Speech Tagging and Named Entity Recognition/9. Part Of Speech Assessment - Solutions.vtt 8.9 kB
  • 2. Python Text Basics/8. Python Text Basics - Assessment Solutions.vtt 8.8 kB
  • 8. Deep Learning for NLP/3. Introduction to Neural Networks.vtt 8.8 kB
  • 3. Natural Language Processing Basics/13. NLP Basics Assessment Solution.vtt 8.7 kB
  • 3. Natural Language Processing Basics/11. Phrase Matching and Vocabulary - Part Two.vtt 8.7 kB
  • 7. Topic Modeling/6. Non-negative Matrix Factorization Overview.vtt 8.5 kB
  • 3. Natural Language Processing Basics/8. Lemmatization.vtt 8.3 kB
  • 7. Topic Modeling/9. Topic Modeling Project - Solutions.vtt 8.0 kB
  • 5. Text Classification/13. Text Classification Assessment Solutions.vtt 7.8 kB
  • 3. Natural Language Processing Basics/6. Tokenization - Part Two.vtt 7.7 kB
  • 4. Part of Speech Tagging and Named Entity Recognition/3. Visualizing Part of Speech.vtt 7.7 kB
  • 5. Text Classification/8. Text Feature Extraction Overview.vtt 7.7 kB
  • 8. Deep Learning for NLP/5. Keras Basics - Part Two.vtt 7.0 kB
  • 8. Deep Learning for NLP/2. The Basic Perceptron Model.vtt 6.9 kB
  • 1. Introduction/1. Course Overview - DO NOT SKIP THIS LECTURE PLEASE. IMPORTANT INFO HERE!.vtt 6.4 kB
  • 6. Semantics and Sentiment Analysis/4. Sentiment Analysis Overview.vtt 6.2 kB
  • 3. Natural Language Processing Basics/9. Stop Words.vtt 5.7 kB
  • 7. Topic Modeling/8. Topic Modeling Project - Overview.vtt 5.3 kB
  • 1. Introduction/5. FAQ - Frequently Asked Questions.html 5.2 kB
  • 1. Introduction/3. Curriculum Overview.vtt 4.4 kB
  • 3. Natural Language Processing Basics/12. NLP Basics Assessment Overview.vtt 4.2 kB
  • 6. Semantics and Sentiment Analysis/7. Sentiment Analysis Project Assessment.vtt 4.1 kB
  • 3. Natural Language Processing Basics/3. What is Natural Language Processing.vtt 4.0 kB
  • 4. Part of Speech Tagging and Named Entity Recognition/8. Part Of Speech Assessment.vtt 3.3 kB
  • 2. Python Text Basics/7. Python Text Basics - Assessment Overview.vtt 3.3 kB
  • 7. Topic Modeling/2. Overview of Topic Modeling.vtt 2.7 kB
  • 5. Text Classification/1. Introduction to Text Classification.vtt 1.1 kB
  • 8. Deep Learning for NLP/1. Introduction to Deep Learning for NLP.vtt 1.1 kB
  • 3. Natural Language Processing Basics/1. Introduction to Natural Language Processing.vtt 866 Bytes
  • 2. Python Text Basics/1. Introduction to Python Text Basics.vtt 795 Bytes
  • 7. Topic Modeling/1. Introduction to Topic Modeling Section.vtt 760 Bytes
  • 4. Part of Speech Tagging and Named Entity Recognition/1. Introduction to Section on POS and NER.vtt 669 Bytes
  • 6. Semantics and Sentiment Analysis/1. Introduction to Semantics and Sentiment Analysis.vtt 581 Bytes
  • 1. Introduction/2. Quick Check.html 150 Bytes
  • 1. Introduction/4.1 Link for .yml file (Should work for all Operating Systems).html 127 Bytes
  • [FreeCourseLab.com].url 126 Bytes
  • 8. Deep Learning for NLP/11.1 End to End Networks.html 97 Bytes

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