[DesireCourse.Net] Udemy - Data Science Natural Language Processing (NLP) in Python

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[DesireCourse.Net] Udemy - Data Science Natural Language Processing (NLP) in Python

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收录时间：2021-03-18
最近下载：2025-02-09

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文件列表

  • 11. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4 195.5 MB
  • 10. Machine Learning Basics Review/3. (Review) Classification in Code.mp4 146.3 MB
  • 3. Decrypting Ciphers/4. Genetic Algorithms.mp4 110.3 MB
  • 11. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
  • 7. Latent Semantic Analysis/2. SVD - The underlying math behind LSA.mp4 82.0 MB
  • 5. Build your own sentiment analyzer/7. How to Improve Sentiment Analysis & FAQ.mp4 81.5 MB
  • 10. Machine Learning Basics Review/2. (Review) What is Classification.mp4 74.1 MB
  • 10. Machine Learning Basics Review/5. (Review) Regression in Code.mp4 72.7 MB
  • 3. Decrypting Ciphers/3. Language Models.mp4 68.8 MB
  • 10. Machine Learning Basics Review/9. (Review) Comparing Different Machine Learning Models.mp4 56.2 MB
  • 10. Machine Learning Basics Review/4. (Review) What is Regression.mp4 52.0 MB
  • 10. Machine Learning Basics Review/1. (Review) Machine Learning Section Introduction.mp4 47.0 MB
  • 11. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
  • 5. Build your own sentiment analyzer/5. Sentiment Analysis in Python using Logistic Regression.mp4 45.7 MB
  • 3. Decrypting Ciphers/11. Code pt 5.mp4 42.9 MB
  • 10. Machine Learning Basics Review/10. (Review) Machine Learning and Deep Learning Future Topics.mp4 42.9 MB
  • 4. Build your own spam detector/4. Naive Bayes Concepts.mp4 41.6 MB
  • 3. Decrypting Ciphers/12. Code pt 6.mp4 41.3 MB
  • 3. Decrypting Ciphers/8. Code pt 2.mp4 41.0 MB
  • 11. Appendix FAQ/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
  • 10. Machine Learning Basics Review/6. (Review) What is a Feature Vector.mp4 39.8 MB
  • 11. Appendix FAQ/12. BONUS Where to get discount coupons and FREE deep learning material.mp4 39.7 MB
  • 11. Appendix FAQ/11. What order should I take your courses in (part 2).mp4 39.5 MB
  • 8. Write your own article spinner/3. More about Language Models.mp4 38.4 MB
  • 4. Build your own spam detector/3. Key Takeaway from Spam Detection Exercise.mp4 32.1 MB
  • 3. Decrypting Ciphers/9. Code pt 3.mp4 31.0 MB
  • 11. Appendix FAQ/10. What order should I take your courses in (part 1).mp4 30.7 MB
  • 4. Build your own spam detector/5. AdaBoost Concepts.mp4 28.1 MB
  • 3. Decrypting Ciphers/1. Section Introduction.mp4 27.6 MB
  • 8. Write your own article spinner/5. Writing an article spinner in Python.mp4 27.2 MB
  • 3. Decrypting Ciphers/10. Code pt 4.mp4 26.9 MB
  • 7. Latent Semantic Analysis/3. Latent Semantic Analysis in Python.mp4 26.7 MB
  • 10. Machine Learning Basics Review/11. (Review) Section Summary.mp4 26.0 MB
  • 10. Machine Learning Basics Review/8. (Review) All Data is the Same.mp4 26.0 MB
  • 11. Appendix FAQ/4. How to Code by Yourself (part 1).mp4 25.7 MB
  • 3. Decrypting Ciphers/13. Section Conclusion.mp4 25.4 MB
  • 8. Write your own article spinner/6. Article Spinner Extension Exercises.mp4 24.8 MB
  • 10. Machine Learning Basics Review/7. (Review) Machine Learning is Nothing but Geometry.mp4 23.8 MB
  • 3. Decrypting Ciphers/5. Code Preparation.mp4 21.7 MB
  • 8. Write your own article spinner/4. Precode Exercises.mp4 20.7 MB
  • 3. Decrypting Ciphers/2. Ciphers.mp4 18.0 MB
  • 7. Latent Semantic Analysis/4. What is Latent Semantic Analysis Used For.mp4 17.7 MB
  • 3. Decrypting Ciphers/7. Code pt 1.mp4 16.7 MB
  • 11. Appendix FAQ/5. How to Code by Yourself (part 2).mp4 15.5 MB
  • 4. 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
  • 11. Appendix FAQ/6. How to Succeed in this Course (Long Version).mp4 13.6 MB
  • 5. Build your own sentiment analyzer/2. Logistic Regression Review.mp4 12.8 MB
  • 7. Latent Semantic Analysis/5. Extending LSA.mp4 11.4 MB
  • 4. Build your own spam detector/7. Spam Detection FAQ (Remedial #1).mp4 11.2 MB
  • 5. Build your own sentiment analyzer/4. Preprocessing Tokens to Vectors.mp4 11.1 MB
  • 4. Build your own spam detector/8. What is a Vector (Remedial #2).mp4 9.5 MB
  • 3. Decrypting Ciphers/13. Section Conclusion.srt 9.4 MB
  • 6. NLTK Exploration/4. Want more NLTK.mp4 8.9 MB
  • 11. Appendix FAQ/9. Python 2 vs Python 3.mp4 8.2 MB
  • 5. 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
  • 6. NLTK Exploration/3. NLTK Exploration Named Entity Recognition.mp4 7.0 MB
  • 4. 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
  • 4. Build your own spam detector/9. SMS Spam Example.mp4 6.0 MB
  • 11. Appendix FAQ/1. What is the Appendix.mp4 5.7 MB
  • 5. Build your own sentiment analyzer/6. Sentiment Analysis Extension.mp4 5.4 MB
  • 5. Build your own sentiment analyzer/1. Description of Sentiment Analyzer.mp4 5.3 MB
  • 8. 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 4.7 MB
  • 9. How to learn more about NLP/1. What we didn't talk about.mp4 4.5 MB
  • 7. Latent Semantic Analysis/1. Latent Semantic Analysis - What does it do.mp4 4.1 MB
  • 8. Write your own article spinner/2. Trigram Model.mp4 4.0 MB
  • 6. NLTK Exploration/2. NLTK Exploration Stemming and Lemmatization.mp4 3.8 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
  • 6. NLTK Exploration/1. NLTK Exploration POS Tagging.mp4 2.1 MB
  • 4. Build your own spam detector/1. Build your own spam detector - description of data.mp4 2.0 MB
  • 4. Build your own spam detector/6. Other types of features.mp4 1.5 MB
  • 3. Decrypting Ciphers/4. Genetic Algorithms.srt 29.6 kB
  • 11. Appendix FAQ/11. What order should I take your courses in (part 2).srt 23.6 kB
  • 11. Appendix FAQ/4. How to Code by Yourself (part 1).srt 23.3 kB
  • 3. Decrypting Ciphers/3. Language Models.srt 21.1 kB
  • 11. Appendix FAQ/2. Windows-Focused Environment Setup 2018.srt 20.6 kB
  • 7. Latent Semantic Analysis/2. SVD - The underlying math behind LSA.srt 20.0 kB
  • 10. Machine Learning Basics Review/4. (Review) What is Regression.srt 17.2 kB
  • 10. Machine Learning Basics Review/3. (Review) Classification in Code.srt 17.2 kB
  • 11. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 17.2 kB
  • 10. Machine Learning Basics Review/2. (Review) What is Classification.srt 16.9 kB
  • 5. Build your own sentiment analyzer/7. How to Improve Sentiment Analysis & FAQ.srt 16.8 kB
  • 5. Build your own sentiment analyzer/5. Sentiment Analysis in Python using Logistic Regression.srt 16.5 kB
  • 11. Appendix FAQ/10. What order should I take your courses in (part 1).srt 16.4 kB
  • 11. Appendix FAQ/6. How to Succeed in this Course (Long Version).srt 15.0 kB
  • 11. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.srt 14.5 kB
  • 11. Appendix FAQ/5. How to Code by Yourself (part 2).srt 13.6 kB
  • 10. Machine Learning Basics Review/9. (Review) Comparing Different Machine Learning Models.srt 13.5 kB
  • 7. Latent Semantic Analysis/4. What is Latent Semantic Analysis Used For.srt 12.8 kB
  • 8. Write your own article spinner/3. More about Language Models.srt 12.6 kB
  • 4. Build your own spam detector/4. Naive Bayes Concepts.srt 12.1 kB
  • 4. Build your own spam detector/7. Spam Detection FAQ (Remedial #1).srt 11.6 kB
  • 4. Build your own spam detector/10. SMS Spam in Code.srt 11.5 kB
  • 10. Machine Learning Basics Review/1. (Review) Machine Learning Section Introduction.srt 11.3 kB
  • 10. Machine Learning Basics Review/5. (Review) Regression in Code.srt 10.1 kB
  • 5. Build your own sentiment analyzer/2. Logistic Regression Review.srt 10.0 kB
  • 8. Write your own article spinner/5. Writing an article spinner in Python.srt 10.0 kB
  • 3. Decrypting Ciphers/8. Code pt 2.srt 9.3 kB
  • 10. Machine Learning Basics Review/6. (Review) What is a Feature Vector.srt 9.1 kB
  • 3. Decrypting Ciphers/11. Code pt 5.srt 8.9 kB
  • 1. Natural Language Processing - What is it used for/2. NLP Applications.srt 8.6 kB
  • 4. Build your own spam detector/9. SMS Spam Example.srt 8.3 kB
  • 10. Machine Learning Basics Review/10. (Review) Machine Learning and Deep Learning Future Topics.srt 8.1 kB
  • 10. Machine Learning Basics Review/11. (Review) Section Summary.srt 8.1 kB
  • 11. Appendix FAQ/12. BONUS Where to get discount coupons and FREE deep learning material.srt 8.1 kB
  • 4. Build your own spam detector/8. What is a Vector (Remedial #2).srt 8.0 kB
  • 4. Build your own spam detector/3. Key Takeaway from Spam Detection Exercise.srt 8.0 kB
  • 5. Build your own sentiment analyzer/4. Preprocessing Tokens to Vectors.srt 7.9 kB
  • 5. Build your own sentiment analyzer/6. Sentiment Analysis Extension.srt 7.8 kB
  • 7. Latent Semantic Analysis/5. Extending LSA.srt 7.8 kB
  • 7. Latent Semantic Analysis/3. Latent Semantic Analysis in Python.srt 7.7 kB
  • 10. Machine Learning Basics Review/8. (Review) All Data is the Same.srt 7.2 kB
  • 3. Decrypting Ciphers/12. Code pt 6.srt 7.2 kB
  • 3. Decrypting Ciphers/5. Code Preparation.srt 6.9 kB
  • 8. Write your own article spinner/6. Article Spinner Extension Exercises.srt 6.9 kB
  • 3. Decrypting Ciphers/1. Section Introduction.srt 6.8 kB
  • 4. Build your own spam detector/5. AdaBoost Concepts.srt 6.5 kB
  • 5. Build your own sentiment analyzer/3. Preprocessing Tokenization.srt 6.3 kB
  • 10. Machine Learning Basics Review/7. (Review) Machine Learning is Nothing but Geometry.srt 6.3 kB
  • 3. Decrypting Ciphers/9. Code pt 3.srt 6.3 kB
  • 11. Appendix FAQ/9. Python 2 vs Python 3.srt 6.2 kB
  • 8. Write your own article spinner/4. Precode Exercises.srt 6.2 kB
  • 4. Build your own spam detector/2. Build your own spam detector using Naive Bayes and AdaBoost - the code.srt 6.0 kB
  • 3. Decrypting Ciphers/10. Code pt 4.srt 5.0 kB
  • 3. Decrypting Ciphers/2. Ciphers.srt 4.9 kB
  • 1. Natural Language Processing - What is it used for/3. Why is NLP hard.srt 4.8 kB
  • 5. Build your own sentiment analyzer/1. Description of Sentiment Analyzer.srt 4.3 kB
  • 3. Decrypting Ciphers/7. Code pt 1.srt 4.2 kB
  • 8. Write your own article spinner/1. Article Spinning Introduction and Markov Models.srt 4.2 kB
  • 1. Natural Language Processing - What is it used for/1. Introduction and Outline.srt 4.1 kB
  • 2. Course Preparation/1. How to Succeed in this Course.srt 4.1 kB
  • 9. How to learn more about NLP/1. What we didn't talk about.srt 3.9 kB
  • 11. Appendix FAQ/1. What is the Appendix.srt 3.8 kB
  • 2. Course Preparation/3. Do you need a review of machine learning.srt 3.7 kB
  • 7. Latent Semantic Analysis/1. Latent Semantic Analysis - What does it do.srt 3.6 kB
  • 2. Course Preparation/2. Where to get the code and data.srt 3.5 kB
  • 1. Natural Language Processing - What is it used for/4. The Central Message of this Course.srt 3.5 kB
  • 8. Write your own article spinner/2. Trigram Model.srt 3.2 kB
  • 4. Build your own spam detector/1. Build your own spam detector - description of data.srt 2.7 kB
  • 6. NLTK Exploration/4. Want more NLTK.srt 2.5 kB
  • 6. NLTK Exploration/3. NLTK Exploration Named Entity Recognition.srt 2.3 kB
  • 6. NLTK Exploration/1. NLTK Exploration POS Tagging.srt 2.0 kB
  • 4. Build your own spam detector/6. Other types of features.srt 1.9 kB
  • 6. NLTK Exploration/2. NLTK Exploration Stemming and Lemmatization.srt 1.7 kB
  • 3. Decrypting Ciphers/6. Link to Cipher Notebook.html 235 Bytes
  • [FreeCourseWorld.Com].url 54 Bytes
  • [DesireCourse.Net].url 51 Bytes
  • [CourseClub.Me].url 48 Bytes
  • 11. Appendix FAQ/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 0 Bytes

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