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

BT种子名称

请保存以下最新地址

BT种子基本信息

种子哈希：44ffa02a7ead9b8cbcc87204e536a1177dbccf21
文档大小：1.8 GB
文档个数：127个文档
下载次数：3134次
下载速度：极快
收录时间：2020-03-26
最近下载：2024-11-04
DMCA/屏蔽：DMCA/屏蔽

下载磁力链接

magnet:?xt=urn:btih:44FFA02A7EAD9B8CBCC87204E536A1177DBCCF21
复制磁力链接到PikPak、utorrent、Bitcomet、迅雷、115、百度网盘等下载工具进行下载。

下载BT种子

磁力链接种子下载迅雷下载二维码 YouTube成人版 91视频 91短视频 51品茶逼哩逼哩萝莉岛欲漫涩草榴社区含羞草抖阴破解版 TikTok成人版成人快手乱伦社区 91AV 暗网禁地

[FreeCourseSite.com] Udemy - Data Science Natural Language Processing (NLP) in Python的二维码

文档列表

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/1. (Review) Machine Learning Section Introduction.mp4 47.0 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).mp4 39.4 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.mp4 32.1 MB
10. Appendix/10. What order should I take your courses in (part 1).mp4 30.7 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
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 14.0 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 11.4 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 3.8 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
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 56.0 kB
10. Appendix/11. What order should I take your courses in (part 2).vtt 42.7 kB
10. Appendix/4. How to Code by Yourself (part 1).vtt 39.8 kB
6. Latent Semantic Analysis/2. SVD - The underlying math behind LSA.vtt 34.7 kB
10. Appendix/2. Windows-Focused Environment Setup 2018.vtt 34.5 kB
9. Machine Learning Basics Review/2. (Review) What is Classification.vtt 29.4 kB
9. Machine Learning Basics Review/3. (Review) Classification in Code.vtt 29.3 kB
4. Build your own sentiment analyzer/7. How to Improve Sentiment Analysis & FAQ.vtt 29.2 kB
9. Machine Learning Basics Review/4. (Review) What is Regression.vtt 28.7 kB
10. Appendix/10. What order should I take your courses in (part 1).vtt 28.7 kB
10. Appendix/6. How to Succeed in this Course (Long Version).vtt 25.1 kB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt 24.1 kB
9. Machine Learning Basics Review/9. (Review) Comparing Different Machine Learning Models.vtt 23.8 kB
10. Appendix/5. How to Code by Yourself (part 2).vtt 23.5 kB
6. Latent Semantic Analysis/4. What is Latent Semantic Analysis Used For.vtt 21.7 kB
7. Write your own article spinner/2. More about Language Models.vtt 21.2 kB
3. Build your own spam detector/7. Spam Detection FAQ (Remedial #1).vtt 21.1 kB
3. Build your own spam detector/4. Naive Bayes Concepts.vtt 21.0 kB
9. Machine Learning Basics Review/1. (Review) Machine Learning Section Introduction.vtt 19.9 kB
3. Build your own spam detector/10. SMS Spam in Code.vtt 19.6 kB
9. Machine Learning Basics Review/5. (Review) Regression in Code.vtt 17.3 kB
4. Build your own sentiment analyzer/2. Logistic Regression Review.vtt 16.9 kB
9. Machine Learning Basics Review/6. (Review) What is a Feature Vector.vtt 16.0 kB
10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 14.9 kB
1. Natural Language Processing - What is it used for/2. NLP Applications.vtt 14.4 kB
4. Build your own sentiment analyzer/5. Sentiment Analysis in Python using Logistic Regression.vtt 14.3 kB
3. Build your own spam detector/9. SMS Spam Example.vtt 14.2 kB
9. Machine Learning Basics Review/10. (Review) Machine Learning and Deep Learning Future Topics.vtt 14.1 kB
3. Build your own spam detector/8. What is a Vector (Remedial #2).vtt 14.1 kB
9. Machine Learning Basics Review/11. (Review) Section Summary.vtt 13.8 kB
6. Latent Semantic Analysis/5. Extending LSA.vtt 13.7 kB
4. Build your own sentiment analyzer/6. Sentiment Analysis Extension.vtt 13.7 kB
3. Build your own spam detector/3. Key Takeaway from Spam Detection Exercise.vtt 13.6 kB
4. Build your own sentiment analyzer/4. Preprocessing Tokens to Vectors.vtt 13.0 kB
9. Machine Learning Basics Review/8. (Review) All Data is the Same.vtt 12.2 kB
7. Write your own article spinner/6. Article Spinner Extension Exercises.vtt 11.8 kB
3. Build your own spam detector/5. AdaBoost Concepts.vtt 11.2 kB
9. Machine Learning Basics Review/7. (Review) Machine Learning is Nothing but Geometry.vtt 10.8 kB
10. Appendix/9. Python 2 vs Python 3.vtt 10.7 kB
7. Write your own article spinner/4. Precode Exercises.vtt 10.4 kB
4. Build your own sentiment analyzer/3. Preprocessing Tokenization.vtt 10.4 kB
3. Build your own spam detector/2. Build your own spam detector using Naive Bayes and AdaBoost - the code.vtt 10.2 kB
7. Write your own article spinner/5. Writing an article spinner in Python.vtt 8.7 kB
1. Natural Language Processing - What is it used for/3. Why is NLP hard.vtt 8.5 kB
1. Natural Language Processing - What is it used for/1. Introduction and Outline.vtt 7.7 kB
4. Build your own sentiment analyzer/1. Description of Sentiment Analyzer.vtt 7.4 kB
2. Course Preparation/1. How to Succeed in this Course.vtt 7.3 kB
6. Latent Semantic Analysis/3. Latent Semantic Analysis in Python.vtt 6.8 kB
1. Natural Language Processing - What is it used for/4. The Central Message of this Course.vtt 6.5 kB
2. Course Preparation/3. Do you need a review of machine learning.vtt 6.3 kB
10. Appendix/1. What is the Appendix.vtt 6.2 kB
2. Course Preparation/2. Where to get the code and data.vtt 5.7 kB
3. Build your own spam detector/1. Build your own spam detector - description of data.vtt 4.7 kB
5. NLTK Exploration/4. Want more NLTK.vtt 4.2 kB
5. NLTK Exploration/1. NLTK Exploration POS Tagging.vtt 3.8 kB
7. Write your own article spinner/1. Article Spinning Introduction and Markov Models.vtt 3.7 kB
8. How to learn more about NLP/1. What we didn't talk about.vtt 3.5 kB
3. Build your own spam detector/6. Other types of features.vtt 3.3 kB
6. Latent Semantic Analysis/1. Latent Semantic Analysis - What does it do.vtt 3.2 kB
7. Write your own article spinner/3. Trigram Model.vtt 2.9 kB
5. NLTK Exploration/2. NLTK Exploration Stemming and Lemmatization.vtt 2.7 kB
5. NLTK Exploration/3. NLTK Exploration Named Entity Recognition.vtt 2.0 kB
[FCS Forum].url 133 Bytes
[FreeCourseSite.com].url 127 Bytes
[CourseClub.NET].url 123 Bytes

==查看完整文档列表==

上一个：[NFI]_Mai-Otome_Zwei_(BD_720p)2.4 GB