[FreeCourseLab.com] Udemy - Data Science Natural Language Processing (NLP) in Python

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[FreeCourseLab.com] Udemy - Data Science Natural Language Processing (NLP) in Python

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种子哈希：6969c3fae0922a0e8b1a1760d46349b8b2515512
文件大小： 1.81G
已经下载：30次
下载速度：极快
收录时间：2021-06-13
最近下载：2024-02-15

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文件列表

  • 10. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.5 MB
  • 9. Machine Learning Basics Review/3. (Review) Classification in Code.mp4 146.3 MB
  • 10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
  • 6. Latent Semantic Analysis/2. SVD - The underlying math behind LSA.mp4 82.0 MB
  • 4. Build your own sentiment analyzer/7. How to Improve Sentiment Analysis & FAQ.mp4 81.5 MB
  • 9. Machine Learning Basics Review/2. (Review) What is Classification.mp4 74.1 MB
  • 9. Machine Learning Basics Review/5. (Review) Regression in Code.mp4 72.7 MB
  • 9. Machine Learning Basics Review/9. (Review) Comparing Different Machine Learning Models.mp4 56.2 MB
  • 9. Machine Learning Basics Review/4. (Review) What is Regression.mp4 52.0 MB
  • 9. Machine Learning Basics Review/4. (Review) What is Regression.vtt 52.0 MB
  • 9. Machine Learning Basics Review/1. (Review) Machine Learning Section Introduction.mp4 47.1 MB
  • 10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
  • 4. Build your own sentiment analyzer/5. Sentiment Analysis in Python using Logistic Regression.mp4 45.7 MB
  • 9. Machine Learning Basics Review/10. (Review) Machine Learning and Deep Learning Future Topics.mp4 42.8 MB
  • 3. Build your own spam detector/4. Naive Bayes Concepts.mp4 41.6 MB
  • 10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
  • 9. Machine Learning Basics Review/6. (Review) What is a Feature Vector.mp4 39.8 MB
  • 10. Appendix/11. What order should I take your courses in (part 2).vtt 39.5 MB
  • 10. Appendix/11. What order should I take your courses in (part 2).mp4 39.5 MB
  • 7. Write your own article spinner/2. More about Language Models.mp4 38.4 MB
  • 3. Build your own spam detector/3. Key Takeaway from Spam Detection Exercise.vtt 32.1 MB
  • 3. Build your own spam detector/3. Key Takeaway from Spam Detection Exercise.mp4 32.1 MB
  • 10. Appendix/10. What order should I take your courses in (part 1).mp4 30.8 MB
  • 10. Appendix/10. What order should I take your courses in (part 1).vtt 30.8 MB
  • 3. Build your own spam detector/5. AdaBoost Concepts.mp4 28.1 MB
  • 7. Write your own article spinner/5. Writing an article spinner in Python.mp4 27.2 MB
  • 6. Latent Semantic Analysis/3. Latent Semantic Analysis in Python.mp4 26.7 MB
  • 6. Latent Semantic Analysis/3. Latent Semantic Analysis in Python.vtt 26.7 MB
  • 9. Machine Learning Basics Review/11. (Review) Section Summary.mp4 26.0 MB
  • 9. Machine Learning Basics Review/8. (Review) All Data is the Same.mp4 26.0 MB
  • 10. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
  • 7. Write your own article spinner/6. Article Spinner Extension Exercises.mp4 24.8 MB
  • 9. Machine Learning Basics Review/7. (Review) Machine Learning is Nothing but Geometry.mp4 23.8 MB
  • 7. Write your own article spinner/4. Precode Exercises.mp4 20.7 MB
  • 6. Latent Semantic Analysis/4. What is Latent Semantic Analysis Used For.mp4 17.7 MB
  • 10. Appendix/5. How to Code by Yourself (part 2).mp4 15.5 MB
  • 3. Build your own spam detector/10. SMS Spam in Code.mp4 14.6 MB
  • 2. Course Preparation/3. Do you need a review of machine learning.mp4 14.1 MB
  • 10. Appendix/6. How to Succeed in this Course (Long Version).mp4 13.6 MB
  • 4. Build your own sentiment analyzer/2. Logistic Regression Review.mp4 12.8 MB
  • 6. Latent Semantic Analysis/5. Extending LSA.mp4 11.5 MB
  • 3. Build your own spam detector/7. Spam Detection FAQ (Remedial #1).mp4 11.2 MB
  • 4. Build your own sentiment analyzer/4. Preprocessing Tokens to Vectors.mp4 11.1 MB
  • 3. Build your own spam detector/8. What is a Vector (Remedial #2).mp4 9.5 MB
  • 5. NLTK Exploration/4. Want more NLTK.mp4 8.9 MB
  • 10. Appendix/9. Python 2 vs Python 3.mp4 8.2 MB
  • 4. Build your own sentiment analyzer/3. Preprocessing Tokenization.mp4 8.1 MB
  • 1. Natural Language Processing - What is it used for/3. Why is NLP hard.mp4 7.5 MB
  • 5. NLTK Exploration/3. NLTK Exploration Named Entity Recognition.mp4 7.0 MB
  • 3. Build your own spam detector/2. Build your own spam detector using Naive Bayes and AdaBoost - the code.mp4 6.9 MB
  • 1. Natural Language Processing - What is it used for/2. NLP Applications.mp4 6.0 MB
  • 3. Build your own spam detector/9. SMS Spam Example.mp4 6.0 MB
  • 10. Appendix/1. What is the Appendix.mp4 5.7 MB
  • 4. Build your own sentiment analyzer/6. Sentiment Analysis Extension.mp4 5.4 MB
  • 4. Build your own sentiment analyzer/1. Description of Sentiment Analyzer.mp4 5.3 MB
  • 7. Write your own article spinner/1. Article Spinning Introduction and Markov Models.mp4 4.9 MB
  • 2. Course Preparation/2. Where to get the code and data.mp4 4.6 MB
  • 8. How to learn more about NLP/1. What we didn't talk about.mp4 4.5 MB
  • 6. Latent Semantic Analysis/1. Latent Semantic Analysis - What does it do.mp4 4.1 MB
  • 7. Write your own article spinner/3. Trigram Model.mp4 4.0 MB
  • 5. NLTK Exploration/2. NLTK Exploration Stemming and Lemmatization.mp4 3.9 MB
  • 2. Course Preparation/1. How to Succeed in this Course.mp4 3.5 MB
  • 1. Natural Language Processing - What is it used for/4. The Central Message of this Course.mp4 3.3 MB
  • 1. Natural Language Processing - What is it used for/1. Introduction and Outline.mp4 2.6 MB
  • 5. NLTK Exploration/1. NLTK Exploration POS Tagging.mp4 2.1 MB
  • 3. Build your own spam detector/1. Build your own spam detector - description of data.mp4 2.0 MB
  • 3. Build your own spam detector/6. Other types of features.mp4 1.5 MB
  • 10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28.4 kB
  • 10. Appendix/4. How to Code by Yourself (part 1).vtt 20.3 kB
  • 10. Appendix/2. Windows-Focused Environment Setup 2018.vtt 17.8 kB
  • 6. Latent Semantic Analysis/2. SVD - The underlying math behind LSA.vtt 17.6 kB
  • 10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 14.9 kB
  • 9. Machine Learning Basics Review/3. (Review) Classification in Code.vtt 14.8 kB
  • 9. Machine Learning Basics Review/2. (Review) What is Classification.vtt 14.8 kB
  • 4. Build your own sentiment analyzer/7. How to Improve Sentiment Analysis & FAQ.vtt 14.7 kB
  • 4. Build your own sentiment analyzer/5. Sentiment Analysis in Python using Logistic Regression.vtt 14.3 kB
  • 10. Appendix/6. How to Succeed in this Course (Long Version).vtt 13.2 kB
  • 10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt 12.5 kB
  • 10. Appendix/5. How to Code by Yourself (part 2).vtt 11.9 kB
  • 9. Machine Learning Basics Review/9. (Review) Comparing Different Machine Learning Models.vtt 11.9 kB
  • 6. Latent Semantic Analysis/4. What is Latent Semantic Analysis Used For.vtt 11.3 kB
  • 7. Write your own article spinner/2. More about Language Models.vtt 11.0 kB
  • 3. Build your own spam detector/4. Naive Bayes Concepts.vtt 10.6 kB
  • 3. Build your own spam detector/7. Spam Detection FAQ (Remedial #1).vtt 10.2 kB
  • 3. Build your own spam detector/10. SMS Spam in Code.vtt 10.0 kB
  • 9. Machine Learning Basics Review/1. (Review) Machine Learning Section Introduction.vtt 9.9 kB
  • 9. Machine Learning Basics Review/5. (Review) Regression in Code.vtt 8.8 kB
  • 4. Build your own sentiment analyzer/2. Logistic Regression Review.vtt 8.7 kB
  • 7. Write your own article spinner/5. Writing an article spinner in Python.vtt 8.7 kB
  • 9. Machine Learning Basics Review/6. (Review) What is a Feature Vector.vtt 8.0 kB
  • 1. Natural Language Processing - What is it used for/2. NLP Applications.vtt 7.5 kB
  • 3. Build your own spam detector/9. SMS Spam Example.vtt 7.3 kB
  • 9. Machine Learning Basics Review/10. (Review) Machine Learning and Deep Learning Future Topics.vtt 7.1 kB
  • 3. Build your own spam detector/8. What is a Vector (Remedial #2).vtt 7.1 kB
  • 9. Machine Learning Basics Review/11. (Review) Section Summary.vtt 7.0 kB
  • 6. Latent Semantic Analysis/5. Extending LSA.vtt 7.0 kB
  • 4. Build your own sentiment analyzer/6. Sentiment Analysis Extension.vtt 6.9 kB
  • 4. Build your own sentiment analyzer/4. Preprocessing Tokens to Vectors.vtt 6.9 kB
  • 9. Machine Learning Basics Review/8. (Review) All Data is the Same.vtt 6.3 kB
  • 7. Write your own article spinner/6. Article Spinner Extension Exercises.vtt 6.1 kB
  • 3. Build your own spam detector/5. AdaBoost Concepts.vtt 5.6 kB
  • 4. Build your own sentiment analyzer/3. Preprocessing Tokenization.vtt 5.6 kB
  • 9. Machine Learning Basics Review/7. (Review) Machine Learning is Nothing but Geometry.vtt 5.5 kB
  • 10. Appendix/9. Python 2 vs Python 3.vtt 5.5 kB
  • 7. Write your own article spinner/4. Precode Exercises.vtt 5.4 kB
  • 3. Build your own spam detector/2. Build your own spam detector using Naive Bayes and AdaBoost - the code.vtt 5.2 kB
  • 1. Natural Language Processing - What is it used for/3. Why is NLP hard.vtt 4.3 kB
  • 4. Build your own sentiment analyzer/1. Description of Sentiment Analyzer.vtt 3.8 kB
  • 7. Write your own article spinner/1. Article Spinning Introduction and Markov Models.vtt 3.7 kB
  • 1. Natural Language Processing - What is it used for/1. Introduction and Outline.vtt 3.7 kB
  • 2. Course Preparation/1. How to Succeed in this Course.vtt 3.6 kB
  • 8. How to learn more about NLP/1. What we didn't talk about.vtt 3.5 kB
  • 10. Appendix/1. What is the Appendix.vtt 3.4 kB
  • 2. Course Preparation/3. Do you need a review of machine learning.vtt 3.3 kB
  • 6. Latent Semantic Analysis/1. Latent Semantic Analysis - What does it do.vtt 3.2 kB
  • 1. Natural Language Processing - What is it used for/4. The Central Message of this Course.vtt 3.1 kB
  • 2. Course Preparation/2. Where to get the code and data.vtt 3.0 kB
  • 7. Write your own article spinner/3. Trigram Model.vtt 2.9 kB
  • 3. Build your own spam detector/1. Build your own spam detector - description of data.vtt 2.4 kB
  • 5. NLTK Exploration/4. Want more NLTK.vtt 2.2 kB
  • 5. NLTK Exploration/3. NLTK Exploration Named Entity Recognition.vtt 2.0 kB
  • 5. NLTK Exploration/1. NLTK Exploration POS Tagging.vtt 1.8 kB
  • 3. Build your own spam detector/6. Other types of features.vtt 1.7 kB
  • 5. NLTK Exploration/2. NLTK Exploration Stemming and Lemmatization.vtt 1.5 kB
  • [FreeCourseLab.com].url 126 Bytes

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