free-course-site.com-udemy-hands-on-natural-language-processing-nlp-using-python

磁力链接/BT种子名称

free-course-site.com-udemy-hands-on-natural-language-processing-nlp-using-python

磁力链接/BT种子简介

种子哈希：53b42ecce3479bd67e85dac151f5b28f3bbac9d8
文件大小： 8.89G
已经下载：6次
下载速度：极快
收录时间：2022-01-24
最近下载：2022-04-05

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:53B42ECCE3479BD67E85DAC151F5B28F3BBAC9D8
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 世界之窗 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 极乐禁地 91短视频 TikTok成人版 PornHub 草榴社区 91未成年 乱伦巴士 呦乐园 萝莉岛

最近搜索

文件列表

  • 6. NLP Core/25. LSA in Python Part 1.mp4 309.9 MB
  • 5. Numpy and Pandas/1. Introduction to Numpy.mp4 294.3 MB
  • 6. NLP Core/21. Understanding the N-Gram Model.mp4 271.8 MB
  • 5. Numpy and Pandas/2. Introduction to Pandas.mp4 263.8 MB
  • 6. NLP Core/16. Text Modelling using TF-IDF Model.mp4 233.9 MB
  • 7. Project 1 - Text Classification/9. Understanding Logistic Regression.mp4 211.4 MB
  • 6. NLP Core/24. Understanding Latent Semantic Analysis.mp4 203.9 MB
  • 6. NLP Core/26. LSA in Python Part 2.mp4 199.5 MB
  • 6. NLP Core/22. Building Character N-Gram Model.mp4 194.7 MB
  • 4. Regular Expressions/5. Shorthand Character Classes.mp4 191.3 MB
  • 3. Python Crash Course/11. List Comprehension.mp4 173.5 MB
  • 10. Word2Vec Analysis/1. Understanding Word Vectors.mp4 168.4 MB
  • 6. NLP Core/23. Building Word N-Gram Model.mp4 168.3 MB
  • 6. NLP Core/11. Text Modelling using Bag of Words Model.mp4 153.2 MB
  • 6. NLP Core/7. Stop word removal using NLTK.mp4 146.6 MB
  • 6. NLP Core/5. Stemming using NLTK.mp4 140.0 MB
  • 8. Project 2 - Twitter Sentiment Analysis/6. Preprocessing the tweets.mp4 139.5 MB
  • 3. Python Crash Course/5. Python Data Structures - Lists.mp4 135.5 MB
  • 3. Python Crash Course/7. Python Data Structures - Dictionaries.mp4 131.1 MB
  • 6. NLP Core/18. Building the TF-IDF Model Part 2.mp4 128.7 MB
  • 6. NLP Core/27. Word Synonyms and Antonyms using NLTK.mp4 123.7 MB
  • 7. Project 1 - Text Classification/6. Transforming data into BOW Model.mp4 120.3 MB
  • 6. NLP Core/17. Building the TF-IDF Model Part 1.mp4 115.2 MB
  • 6. NLP Core/19. Building the TF-IDF Model Part 3.mp4 115.2 MB
  • 6. NLP Core/8. Parts Of Speech Tagging.mp4 114.4 MB
  • 10. Word2Vec Analysis/6. Improving the Model.mp4 113.5 MB
  • 6. NLP Core/15. Building the BOW Model Part 4.mp4 113.3 MB
  • 6. NLP Core/4. Introduction to Stemming and Lemmatization.mp4 112.8 MB
  • 8. Project 2 - Twitter Sentiment Analysis/8. Plotting the results.mp4 107.7 MB
  • 9. Project 3 - Text Summarization/7. Calculating the sentence scores.mp4 104.7 MB
  • 3. Python Crash Course/8. Console and File IO in Python.mp4 101.7 MB
  • 7. Project 1 - Text Classification/12. Saving our Model.mp4 101.3 MB
  • 9. Project 3 - Text Summarization/1. Understanding Text Summarization.mp4 100.3 MB
  • 9. Project 3 - Text Summarization/3. Parsing the data using Beautiful Soup.mp4 98.8 MB
  • 3. Python Crash Course/10. Introduction to Classes and Objects.mp4 96.9 MB
  • 6. NLP Core/28. Word Negation Tracking in Python Part 1.mp4 95.1 MB
  • 6. NLP Core/12. Building the BOW Model Part 1.mp4 92.9 MB
  • 7. Project 1 - Text Classification/11. Testing Model performance.mp4 88.1 MB
  • 6. NLP Core/13. Building the BOW Model Part 2.mp4 86.2 MB
  • 4. Regular Expressions/3. Finding Patterns in Text Part 2.mp4 85.4 MB
  • 8. Project 2 - Twitter Sentiment Analysis/4. Fetching real time tweets.mp4 84.9 MB
  • 4. Regular Expressions/2. Finding Patterns in Text Part 1.mp4 83.4 MB
  • 6. NLP Core/14. Building the BOW Model Part 3.mp4 80.7 MB
  • 9. Project 3 - Text Summarization/8. Getting the summary.mp4 80.7 MB
  • 3. Python Crash Course/9. Introduction to Functions.mp4 80.5 MB
  • 6. NLP Core/6. Lemmatization using NLTK.mp4 80.2 MB
  • 1. Introduction to the Course/1. What is NLP.mp4 79.4 MB
  • 6. NLP Core/2. Tokenizing Words and Sentences.mp4 78.3 MB
  • 7. Project 1 - Text Classification/8. Creating training and test set.mp4 75.3 MB
  • 4. Regular Expressions/7. Preprocessing using Regex.mp4 75.1 MB
  • 7. Project 1 - Text Classification/4. Persisting the dataset.mp4 75.1 MB
  • 7. Project 1 - Text Classification/5. Preprocessing the data.mp4 70.7 MB
  • 3. Python Crash Course/3. Introduction to Loops.mp4 67.9 MB
  • 6. NLP Core/20. Building the TF-IDF Model Part 4.mp4 67.7 MB
  • 3. Python Crash Course/2. Conditional Statements.mp4 66.9 MB
  • 4. Regular Expressions/1. Introduction to Regular Expressions.mp4 65.9 MB
  • 7. Project 1 - Text Classification/1. Getting the data for Text Classification.mp4 65.1 MB
  • 3. Python Crash Course/4. Loop Control Statements.mp4 65.0 MB
  • 3. Python Crash Course/6. Python Data Structures - Tuples.mp4 63.9 MB
  • 3. Python Crash Course/1. Variables and Operations in Python.mp4 63.2 MB
  • 6. NLP Core/29. Word Negation Tracking in Python Part 2.mp4 61.5 MB
  • 9. Project 3 - Text Summarization/6. Building the histogram.mp4 61.4 MB
  • 7. Project 1 - Text Classification/3. Importing the dataset.mp4 60.3 MB
  • 7. Project 1 - Text Classification/13. Importing and using our Model.mp4 58.8 MB
  • 6. NLP Core/10. Named Entity Recognition.mp4 58.8 MB
  • 10. Word2Vec Analysis/2. Importing the data.mp4 57.6 MB
  • 10. Word2Vec Analysis/5. Testing Model Performance.mp4 57.1 MB
  • 4. Regular Expressions/4. Substituting Patterns in Text.mp4 56.9 MB
  • 9. Project 3 - Text Summarization/5. Tokenizing Article into sentences.mp4 53.1 MB
  • 10. Word2Vec Analysis/7. Exploring Pre-trained Models.mp4 52.9 MB
  • 9. Project 3 - Text Summarization/4. Preprocessing the data.mp4 50.6 MB
  • 7. Project 1 - Text Classification/7. Transform BOW model into TF-IDF Model.mp4 49.7 MB
  • 2. Getting the required softwares/3. A tour of Spyder IDE.mp4 49.1 MB
  • 8. Project 2 - Twitter Sentiment Analysis/3. Client Authentication.mp4 49.0 MB
  • 9. Project 3 - Text Summarization/2. Fetching article data from the web.mp4 46.0 MB
  • 10. Word2Vec Analysis/3. Preparing the data.mp4 40.4 MB
  • 8. Project 2 - Twitter Sentiment Analysis/7. Predicting sentiments of tweets.mp4 40.0 MB
  • 8. Project 2 - Twitter Sentiment Analysis/5. Loading TF-IDF Model and Classifier.mp4 37.8 MB
  • 8. Project 2 - Twitter Sentiment Analysis/2. Initializing Tokens.mp4 36.8 MB
  • 10. Word2Vec Analysis/4. Training the Word2Vec Model.mp4 35.5 MB
  • 2. Getting the required softwares/1. Installing Anaconda Python.mp4 35.0 MB
  • 7. Project 1 - Text Classification/10. Training our classifier.mp4 32.2 MB
  • 6. NLP Core/1. Installing NLTK in Python.mp4 30.7 MB
  • 8. Project 2 - Twitter Sentiment Analysis/1. Setting up Twitter Application.mp4 29.7 MB
  • 1. Introduction to the Course/2. Getting the Course Resources.mp4 19.1 MB
  • .____padding_file/2 4.2 MB
  • .____padding_file/4 4.2 MB
  • .____padding_file/3 4.2 MB
  • .____padding_file/106 4.2 MB
  • .____padding_file/51 4.2 MB
  • .____padding_file/58 4.2 MB
  • .____padding_file/96 4.2 MB
  • .____padding_file/268 4.2 MB
  • .____padding_file/74 4.2 MB
  • .____padding_file/274 4.2 MB
  • .____padding_file/47 4.2 MB
  • .____padding_file/218 4.2 MB
  • .____padding_file/272 4.2 MB
  • .____padding_file/57 4.2 MB
  • .____padding_file/28 4.2 MB
  • .____padding_file/64 4.2 MB
  • .____padding_file/56 4.2 MB
  • .____padding_file/22 4.2 MB
  • .____padding_file/27 4.2 MB
  • .____padding_file/63 4.2 MB
  • .____padding_file/21 4.2 MB
  • .____padding_file/142 4.2 MB
  • .____padding_file/234 4.2 MB
  • .____padding_file/89 4.2 MB
  • .____padding_file/141 4.2 MB
  • .____padding_file/246 4.2 MB
  • .____padding_file/139 4.2 MB
  • .____padding_file/227 4.2 MB
  • .____padding_file/88 4.2 MB
  • .____padding_file/249 4.2 MB
  • .____padding_file/267 4.2 MB
  • .____padding_file/16 4.2 MB
  • .____padding_file/245 4.2 MB
  • .____padding_file/138 4.2 MB
  • .____padding_file/145 4.2 MB
  • .____padding_file/73 4.2 MB
  • .____padding_file/10 4.2 MB
  • .____padding_file/273 4.2 MB
  • .____padding_file/266 4.2 MB
  • .____padding_file/248 4.2 MB
  • .____padding_file/226 4.2 MB
  • .____padding_file/15 4.2 MB
  • .____padding_file/190 4.2 MB
  • .____padding_file/13 4.2 MB
  • .____padding_file/187 4.2 MB
  • .____padding_file/154 4.2 MB
  • .____padding_file/252 4.2 MB
  • .____padding_file/163 4.2 MB
  • .____padding_file/144 4.2 MB
  • .____padding_file/9 4.2 MB
  • .____padding_file/169 4.2 MB
  • .____padding_file/72 4.2 MB
  • .____padding_file/92 4.2 MB
  • .____padding_file/240 4.2 MB
  • .____padding_file/258 4.2 MB
  • .____padding_file/83 4.2 MB
  • .____padding_file/166 4.2 MB
  • .____padding_file/189 4.2 MB
  • .____padding_file/12 4.2 MB
  • .____padding_file/271 4.2 MB
  • .____padding_file/153 4.2 MB
  • .____padding_file/186 4.2 MB
  • .____padding_file/34 4.2 MB
  • .____padding_file/162 4.2 MB
  • .____padding_file/251 4.2 MB
  • .____padding_file/136 4.2 MB
  • .____padding_file/80 4.2 MB
  • .____padding_file/91 4.2 MB
  • .____padding_file/168 4.2 MB
  • .____padding_file/77 4.2 MB
  • .____padding_file/19 4.2 MB
  • .____padding_file/239 4.2 MB
  • .____padding_file/151 4.2 MB
  • .____padding_file/257 4.2 MB
  • .____padding_file/157 4.2 MB
  • .____padding_file/165 4.2 MB
  • .____padding_file/82 4.2 MB
  • .____padding_file/25 4.2 MB
  • .____padding_file/109 4.2 MB
  • .____padding_file/270 4.2 MB
  • .____padding_file/121 4.2 MB
  • .____padding_file/33 4.2 MB
  • .____padding_file/67 4.2 MB
  • .____padding_file/79 4.2 MB
  • .____padding_file/135 4.2 MB
  • .____padding_file/76 4.2 MB
  • .____padding_file/54 4.2 MB
  • .____padding_file/61 4.2 MB
  • .____padding_file/148 4.2 MB
  • .____padding_file/18 4.2 MB
  • .____padding_file/150 4.2 MB
  • .____padding_file/233 4.2 MB
  • .____padding_file/70 4.2 MB
  • .____padding_file/156 4.2 MB
  • .____padding_file/50 4.2 MB
  • .____padding_file/108 4.2 MB
  • .____padding_file/255 4.2 MB
  • .____padding_file/43 4.2 MB
  • .____padding_file/24 4.2 MB
  • .____padding_file/217 4.2 MB
  • .____padding_file/120 4.2 MB
  • .____padding_file/66 4.2 MB
  • .____padding_file/178 4.2 MB
  • .____padding_file/130 4.2 MB
  • .____padding_file/184 4.2 MB
  • .____padding_file/172 4.2 MB
  • .____padding_file/224 4.2 MB
  • .____padding_file/230 4.2 MB
  • .____padding_file/31 4.2 MB
  • .____padding_file/60 4.2 MB
  • .____padding_file/53 4.2 MB
  • .____padding_file/69 4.2 MB
  • .____padding_file/232 4.2 MB
  • .____padding_file/147 4.2 MB
  • .____padding_file/254 4.2 MB
  • .____padding_file/49 4.2 MB
  • .____padding_file/42 4.2 MB
  • .____padding_file/216 4.2 MB
  • .____padding_file/115 4.2 MB
  • .____padding_file/243 4.2 MB
  • .____padding_file/177 4.2 MB
  • .____padding_file/102 4.2 MB
  • .____padding_file/181 4.2 MB
  • .____padding_file/99 4.2 MB
  • .____padding_file/129 4.2 MB
  • .____padding_file/183 4.2 MB
  • .____padding_file/127 4.2 MB
  • .____padding_file/171 4.2 MB
  • .____padding_file/223 4.2 MB
  • .____padding_file/237 4.2 MB
  • .____padding_file/86 4.2 MB
  • .____padding_file/112 4.2 MB
  • .____padding_file/229 4.2 MB
  • .____padding_file/40 4.2 MB
  • .____padding_file/30 4.2 MB
  • .____padding_file/221 4.2 MB
  • .____padding_file/114 4.2 MB
  • .____padding_file/101 4.2 MB
  • .____padding_file/180 4.2 MB
  • .____padding_file/242 4.2 MB
  • .____padding_file/37 4.2 MB
  • .____padding_file/98 4.2 MB
  • .____padding_file/126 4.2 MB
  • .____padding_file/85 4.2 MB
  • .____padding_file/236 4.2 MB
  • .____padding_file/111 4.2 MB
  • .____padding_file/39 4.2 MB
  • .____padding_file/220 4.2 MB
  • .____padding_file/36 4.2 MB
  • .____padding_file/6 4.2 MB
  • .____padding_file/214 4.2 MB
  • .____padding_file/211 4.2 MB
  • .____padding_file/124 4.2 MB
  • .____padding_file/213 4.2 MB
  • .____padding_file/160 4.2 MB
  • .____padding_file/199 4.2 MB
  • .____padding_file/208 4.2 MB
  • .____padding_file/210 4.2 MB
  • .____padding_file/118 4.2 MB
  • .____padding_file/133 4.2 MB
  • .____padding_file/123 4.2 MB
  • .____padding_file/105 4.2 MB
  • .____padding_file/159 4.2 MB
  • .____padding_file/198 4.2 MB
  • .____padding_file/207 4.2 MB
  • .____padding_file/46 4.2 MB
  • .____padding_file/132 4.2 MB
  • .____padding_file/117 4.2 MB
  • .____padding_file/104 4.2 MB
  • .____padding_file/202 4.2 MB
  • .____padding_file/45 4.2 MB
  • .____padding_file/196 4.2 MB
  • .____padding_file/95 4.2 MB
  • .____padding_file/175 4.2 MB
  • .____padding_file/201 4.2 MB
  • .____padding_file/195 4.2 MB
  • .____padding_file/94 4.2 MB
  • .____padding_file/174 4.2 MB
  • .____padding_file/205 4.2 MB
  • .____padding_file/261 4.2 MB
  • .____padding_file/193 4.2 MB
  • .____padding_file/264 4.2 MB
  • .____padding_file/204 4.2 MB
  • .____padding_file/192 4.2 MB
  • .____padding_file/260 4.2 MB
  • .____padding_file/263 4.2 MB
  • .____padding_file/20 4.2 MB
  • .____padding_file/1 4.2 MB
  • .____padding_file/65 4.1 MB
  • .____padding_file/170 4.1 MB
  • .____padding_file/155 4.1 MB
  • .____padding_file/0 4.1 MB
  • .____padding_file/71 4.1 MB
  • .____padding_file/146 4.0 MB
  • .____padding_file/244 3.9 MB
  • .____padding_file/97 3.9 MB
  • .____padding_file/8 3.8 MB
  • .____padding_file/100 3.8 MB
  • .____padding_file/225 3.7 MB
  • .____padding_file/197 3.7 MB
  • .____padding_file/161 3.6 MB
  • .____padding_file/188 3.6 MB
  • .____padding_file/131 3.5 MB
  • .____padding_file/68 3.5 MB
  • .____padding_file/259 3.5 MB
  • .____padding_file/128 3.4 MB
  • .____padding_file/110 3.4 MB
  • .____padding_file/119 3.2 MB
  • .____padding_file/17 3.2 MB
  • .____padding_file/256 3.2 MB
  • .____padding_file/167 3.1 MB
  • .____padding_file/125 3.1 MB
  • .____padding_file/23 3.1 MB
  • .____padding_file/122 3.1 MB
  • .____padding_file/231 3.0 MB
  • .____padding_file/116 2.9 MB
  • .____padding_file/152 2.8 MB
  • .____padding_file/265 2.7 MB
  • .____padding_file/38 2.7 MB
  • .____padding_file/103 2.7 MB
  • .____padding_file/75 2.6 MB
  • .____padding_file/222 2.6 MB
  • .____padding_file/93 2.5 MB
  • .____padding_file/194 2.4 MB
  • .____padding_file/140 2.3 MB
  • .____padding_file/182 2.3 MB
  • .____padding_file/176 2.2 MB
  • .____padding_file/209 2.1 MB
  • .____padding_file/113 2.1 MB
  • .____padding_file/158 2.0 MB
  • .____padding_file/59 2.0 MB
  • .____padding_file/26 2.0 MB
  • .____padding_file/164 1.9 MB
  • .____padding_file/55 1.9 MB
  • .____padding_file/206 1.8 MB
  • .____padding_file/41 1.8 MB
  • .____padding_file/241 1.8 MB
  • .____padding_file/149 1.7 MB
  • .____padding_file/44 1.6 MB
  • .____padding_file/200 1.6 MB
  • .____padding_file/143 1.6 MB
  • .____padding_file/137 1.6 MB
  • .____padding_file/250 1.5 MB
  • .____padding_file/185 1.4 MB
  • .____padding_file/215 1.4 MB
  • .____padding_file/247 1.4 MB
  • .____padding_file/84 1.4 MB
  • .____padding_file/62 1.4 MB
  • .____padding_file/14 1.4 MB
  • .____padding_file/212 1.3 MB
  • .____padding_file/179 1.3 MB
  • .____padding_file/29 1.3 MB
  • .____padding_file/269 1.2 MB
  • .____padding_file/32 1.2 MB
  • .____padding_file/134 1.1 MB
  • .____padding_file/173 1.0 MB
  • .____padding_file/11 959.4 kB
  • .____padding_file/191 857.6 kB
  • .____padding_file/87 652.8 kB
  • .____padding_file/81 649.4 kB
  • .____padding_file/35 524.6 kB
  • .____padding_file/219 473.7 kB
  • .____padding_file/203 463.0 kB
  • .____padding_file/262 401.3 kB
  • .____padding_file/78 385.6 kB
  • .____padding_file/48 378.2 kB
  • .____padding_file/235 335.6 kB
  • .____padding_file/52 267.3 kB
  • .____padding_file/90 243.6 kB
  • .____padding_file/107 236.5 kB
  • .____padding_file/228 205.8 kB
  • .____padding_file/253 182.5 kB
  • FreeCourseSite.com-Udemy - Hands On Natural Language Processing (NLP) using Python.torrent 106.8 kB
  • .____padding_file/238 94.8 kB
  • FreeCourseSite.com-Udemy - Hands On Natural Language Processing (NLP) using Python_torrent.txt 33.8 kB
  • 5. Numpy and Pandas/2. Introduction to Pandas.srt 29.3 kB
  • 5. Numpy and Pandas/1. Introduction to Numpy.srt 27.7 kB
  • 6. NLP Core/21. Understanding the N-Gram Model.srt 27.7 kB
  • 6. NLP Core/25. LSA in Python Part 1.srt 26.5 kB
  • 5. Numpy and Pandas/2. Introduction to Pandas.vtt 25.3 kB
  • 6. NLP Core/21. Understanding the N-Gram Model.vtt 24.1 kB
  • 5. Numpy and Pandas/1. Introduction to Numpy.vtt 24.0 kB
  • 6. NLP Core/25. LSA in Python Part 1.vtt 22.9 kB
  • 6. NLP Core/16. Text Modelling using TF-IDF Model.srt 22.6 kB
  • 7. Project 1 - Text Classification/9. Understanding Logistic Regression.srt 20.9 kB
  • 6. NLP Core/22. Building Character N-Gram Model.srt 20.7 kB
  • 6. NLP Core/24. Understanding Latent Semantic Analysis.srt 19.7 kB
  • 6. NLP Core/16. Text Modelling using TF-IDF Model.vtt 19.6 kB
  • 7. Project 1 - Text Classification/9. Understanding Logistic Regression.vtt 18.3 kB
  • 6. NLP Core/22. Building Character N-Gram Model.vtt 18.0 kB
  • 4. Regular Expressions/5. Shorthand Character Classes.srt 17.7 kB
  • 6. NLP Core/24. Understanding Latent Semantic Analysis.vtt 17.2 kB
  • 3. Python Crash Course/11. List Comprehension.srt 17.0 kB
  • 3. Python Crash Course/5. Python Data Structures - Lists.srt 16.4 kB
  • 10. Word2Vec Analysis/1. Understanding Word Vectors.srt 16.4 kB
  • 4. Regular Expressions/5. Shorthand Character Classes.vtt 15.4 kB
  • 6. NLP Core/26. LSA in Python Part 2.srt 15.2 kB
  • 6. NLP Core/23. Building Word N-Gram Model.srt 15.1 kB
  • 6. NLP Core/11. Text Modelling using Bag of Words Model.srt 15.1 kB
  • 3. Python Crash Course/11. List Comprehension.vtt 14.7 kB
  • 3. Python Crash Course/7. Python Data Structures - Dictionaries.srt 14.6 kB
  • 10. Word2Vec Analysis/1. Understanding Word Vectors.vtt 14.3 kB
  • 3. Python Crash Course/5. Python Data Structures - Lists.vtt 14.3 kB
  • 6. NLP Core/27. Word Synonyms and Antonyms using NLTK.srt 13.5 kB
  • 6. NLP Core/26. LSA in Python Part 2.vtt 13.2 kB
  • 6. NLP Core/23. Building Word N-Gram Model.vtt 13.2 kB
  • 6. NLP Core/11. Text Modelling using Bag of Words Model.vtt 13.1 kB
  • 6. NLP Core/28. Word Negation Tracking in Python Part 1.srt 13.0 kB
  • 3. Python Crash Course/7. Python Data Structures - Dictionaries.vtt 12.7 kB
  • 6. NLP Core/27. Word Synonyms and Antonyms using NLTK.vtt 11.7 kB
  • 6. NLP Core/28. Word Negation Tracking in Python Part 1.vtt 11.3 kB
  • free-course-site.com-udemy-hands-on-natural-language-processing-nlp-using-python_meta.sqlite 11.3 kB
  • 4. Regular Expressions/2. Finding Patterns in Text Part 1.srt 11.2 kB
  • 6. NLP Core/4. Introduction to Stemming and Lemmatization.srt 10.3 kB
  • 4. Regular Expressions/3. Finding Patterns in Text Part 2.srt 10.2 kB
  • 3. Python Crash Course/3. Introduction to Loops.srt 10.1 kB
  • 9. Project 3 - Text Summarization/1. Understanding Text Summarization.srt 10.0 kB
  • 7. Project 1 - Text Classification/6. Transforming data into BOW Model.srt 10.0 kB
  • 3. Python Crash Course/8. Console and File IO in Python.srt 10.0 kB
  • 3. Python Crash Course/1. Variables and Operations in Python.srt 9.7 kB
  • 4. Regular Expressions/2. Finding Patterns in Text Part 1.vtt 9.7 kB
  • 9. Project 3 - Text Summarization/3. Parsing the data using Beautiful Soup.srt 9.7 kB
  • 6. NLP Core/18. Building the TF-IDF Model Part 2.srt 9.6 kB
  • 3. Python Crash Course/10. Introduction to Classes and Objects.srt 9.6 kB
  • 3. Python Crash Course/4. Loop Control Statements.srt 9.6 kB
  • 6. NLP Core/4. Introduction to Stemming and Lemmatization.vtt 9.0 kB
  • 8. Project 2 - Twitter Sentiment Analysis/8. Plotting the results.srt 8.9 kB
  • 4. Regular Expressions/3. Finding Patterns in Text Part 2.vtt 8.8 kB
  • 6. NLP Core/7. Stop word removal using NLTK.srt 8.8 kB
  • 3. Python Crash Course/3. Introduction to Loops.vtt 8.8 kB
  • 7. Project 1 - Text Classification/6. Transforming data into BOW Model.vtt 8.8 kB
  • 9. Project 3 - Text Summarization/1. Understanding Text Summarization.vtt 8.7 kB
  • 6. NLP Core/5. Stemming using NLTK.srt 8.7 kB
  • 6. NLP Core/15. Building the BOW Model Part 4.srt 8.6 kB
  • 3. Python Crash Course/8. Console and File IO in Python.vtt 8.6 kB
  • 6. NLP Core/19. Building the TF-IDF Model Part 3.srt 8.6 kB
  • 3. Python Crash Course/9. Introduction to Functions.srt 8.5 kB
  • 3. Python Crash Course/1. Variables and Operations in Python.vtt 8.5 kB
  • 6. NLP Core/18. Building the TF-IDF Model Part 2.vtt 8.4 kB
  • 3. Python Crash Course/10. Introduction to Classes and Objects.vtt 8.4 kB
  • 6. NLP Core/17. Building the TF-IDF Model Part 1.srt 8.4 kB
  • 9. Project 3 - Text Summarization/3. Parsing the data using Beautiful Soup.vtt 8.4 kB
  • 3. Python Crash Course/4. Loop Control Statements.vtt 8.3 kB
  • 6. NLP Core/29. Word Negation Tracking in Python Part 2.srt 8.3 kB
  • 4. Regular Expressions/4. Substituting Patterns in Text.srt 8.3 kB
  • 4. Regular Expressions/7. Preprocessing using Regex.srt 8.2 kB
  • 9. Project 3 - Text Summarization/7. Calculating the sentence scores.srt 8.1 kB
  • 10. Word2Vec Analysis/6. Improving the Model.srt 8.0 kB
  • 6. NLP Core/8. Parts Of Speech Tagging.srt 8.0 kB
  • 7. Project 1 - Text Classification/12. Saving our Model.srt 7.9 kB
  • 1. Introduction to the Course/1. What is NLP.srt 7.8 kB
  • 7. Project 1 - Text Classification/1. Getting the data for Text Classification.srt 7.8 kB
  • 8. Project 2 - Twitter Sentiment Analysis/8. Plotting the results.vtt 7.8 kB
  • 6. NLP Core/7. Stop word removal using NLTK.vtt 7.7 kB
  • 6. NLP Core/5. Stemming using NLTK.vtt 7.6 kB
  • 6. NLP Core/15. Building the BOW Model Part 4.vtt 7.5 kB
  • 6. NLP Core/19. Building the TF-IDF Model Part 3.vtt 7.5 kB
  • 3. Python Crash Course/9. Introduction to Functions.vtt 7.4 kB
  • 6. NLP Core/17. Building the TF-IDF Model Part 1.vtt 7.4 kB
  • 7. Project 1 - Text Classification/11. Testing Model performance.srt 7.4 kB
  • 3. Python Crash Course/6. Python Data Structures - Tuples.srt 7.2 kB
  • 6. NLP Core/29. Word Negation Tracking in Python Part 2.vtt 7.2 kB
  • 8. Project 2 - Twitter Sentiment Analysis/6. Preprocessing the tweets.srt 7.1 kB
  • 4. Regular Expressions/4. Substituting Patterns in Text.vtt 7.1 kB
  • 3. Python Crash Course/2. Conditional Statements.srt 7.1 kB
  • 9. Project 3 - Text Summarization/7. Calculating the sentence scores.vtt 7.1 kB
  • 4. Regular Expressions/7. Preprocessing using Regex.vtt 7.1 kB
  • 6. NLP Core/10. Named Entity Recognition.srt 7.0 kB
  • 7. Project 1 - Text Classification/12. Saving our Model.vtt 6.9 kB
  • 6. NLP Core/8. Parts Of Speech Tagging.vtt 6.9 kB
  • 10. Word2Vec Analysis/7. Exploring Pre-trained Models.srt 6.9 kB
  • 8. Project 2 - Twitter Sentiment Analysis/4. Fetching real time tweets.srt 6.9 kB
  • 10. Word2Vec Analysis/6. Improving the Model.vtt 6.9 kB
  • 7. Project 1 - Text Classification/1. Getting the data for Text Classification.vtt 6.8 kB
  • 1. Introduction to the Course/1. What is NLP.vtt 6.8 kB
  • 7. Project 1 - Text Classification/3. Importing the dataset.srt 6.8 kB
  • 10. Word2Vec Analysis/2. Importing the data.srt 6.6 kB
  • 7. Project 1 - Text Classification/4. Persisting the dataset.srt 6.6 kB
  • 7. Project 1 - Text Classification/11. Testing Model performance.vtt 6.4 kB
  • 4. Regular Expressions/1. Introduction to Regular Expressions.srt 6.3 kB
  • 3. Python Crash Course/6. Python Data Structures - Tuples.vtt 6.3 kB
  • 2. Getting the required softwares/3. A tour of Spyder IDE.srt 6.2 kB
  • 3. Python Crash Course/2. Conditional Statements.vtt 6.2 kB
  • 8. Project 2 - Twitter Sentiment Analysis/6. Preprocessing the tweets.vtt 6.2 kB
  • 7. Project 1 - Text Classification/5. Preprocessing the data.srt 6.2 kB
  • 6. NLP Core/13. Building the BOW Model Part 2.srt 6.2 kB
  • 6. NLP Core/10. Named Entity Recognition.vtt 6.2 kB
  • 9. Project 3 - Text Summarization/8. Getting the summary.srt 6.1 kB
  • 10. Word2Vec Analysis/7. Exploring Pre-trained Models.vtt 6.1 kB
  • 9. Project 3 - Text Summarization/2. Fetching article data from the web.srt 6.0 kB
  • 8. Project 2 - Twitter Sentiment Analysis/4. Fetching real time tweets.vtt 6.0 kB
  • 7. Project 1 - Text Classification/3. Importing the dataset.vtt 5.9 kB
  • 6. NLP Core/14. Building the BOW Model Part 3.srt 5.9 kB
  • 7. Project 1 - Text Classification/8. Creating training and test set.srt 5.8 kB
  • 7. Project 1 - Text Classification/4. Persisting the dataset.vtt 5.8 kB
  • 10. Word2Vec Analysis/2. Importing the data.vtt 5.7 kB
  • 6. NLP Core/12. Building the BOW Model Part 1.srt 5.6 kB
  • 9. Project 3 - Text Summarization/6. Building the histogram.srt 5.6 kB
  • 4. Regular Expressions/1. Introduction to Regular Expressions.vtt 5.5 kB
  • 6. NLP Core/2. Tokenizing Words and Sentences.srt 5.5 kB
  • 6. NLP Core/1. Installing NLTK in Python.srt 5.4 kB
  • 2. Getting the required softwares/3. A tour of Spyder IDE.vtt 5.4 kB
  • 8. Project 2 - Twitter Sentiment Analysis/2. Initializing Tokens.srt 5.4 kB
  • 6. NLP Core/20. Building the TF-IDF Model Part 4.srt 5.4 kB
  • 6. NLP Core/13. Building the BOW Model Part 2.vtt 5.4 kB
  • 7. Project 1 - Text Classification/5. Preprocessing the data.vtt 5.4 kB
  • 9. Project 3 - Text Summarization/8. Getting the summary.vtt 5.3 kB
  • 9. Project 3 - Text Summarization/2. Fetching article data from the web.vtt 5.3 kB
  • 7. Project 1 - Text Classification/8. Creating training and test set.vtt 5.1 kB
  • 7. Project 1 - Text Classification/13. Importing and using our Model.srt 5.1 kB
  • 6. NLP Core/14. Building the BOW Model Part 3.vtt 5.1 kB
  • 8. Project 2 - Twitter Sentiment Analysis/1. Setting up Twitter Application.srt 5.1 kB
  • 10. Word2Vec Analysis/5. Testing Model Performance.srt 5.1 kB
  • 6. NLP Core/12. Building the BOW Model Part 1.vtt 4.9 kB
  • 9. Project 3 - Text Summarization/6. Building the histogram.vtt 4.9 kB
  • 6. NLP Core/1. Installing NLTK in Python.vtt 4.8 kB
  • 6. NLP Core/2. Tokenizing Words and Sentences.vtt 4.8 kB
  • 8. Project 2 - Twitter Sentiment Analysis/2. Initializing Tokens.vtt 4.7 kB
  • 6. NLP Core/20. Building the TF-IDF Model Part 4.vtt 4.7 kB
  • 8. Project 2 - Twitter Sentiment Analysis/3. Client Authentication.srt 4.7 kB
  • 6. NLP Core/6. Lemmatization using NLTK.srt 4.6 kB
  • 9. Project 3 - Text Summarization/5. Tokenizing Article into sentences.srt 4.6 kB
  • 2. Getting the required softwares/1. Installing Anaconda Python.srt 4.6 kB
  • 8. Project 2 - Twitter Sentiment Analysis/1. Setting up Twitter Application.vtt 4.4 kB
  • 7. Project 1 - Text Classification/13. Importing and using our Model.vtt 4.4 kB
  • 10. Word2Vec Analysis/5. Testing Model Performance.vtt 4.4 kB
  • 10. Word2Vec Analysis/3. Preparing the data.srt 4.2 kB
  • 9. Project 3 - Text Summarization/4. Preprocessing the data.srt 4.2 kB
  • 8. Project 2 - Twitter Sentiment Analysis/3. Client Authentication.vtt 4.1 kB
  • 2. Getting the required softwares/1. Installing Anaconda Python.vtt 4.0 kB
  • 9. Project 3 - Text Summarization/5. Tokenizing Article into sentences.vtt 4.0 kB
  • 7. Project 1 - Text Classification/7. Transform BOW model into TF-IDF Model.srt 4.0 kB
  • 6. NLP Core/6. Lemmatization using NLTK.vtt 3.9 kB
  • 10. Word2Vec Analysis/3. Preparing the data.vtt 3.7 kB
  • 9. Project 3 - Text Summarization/4. Preprocessing the data.vtt 3.6 kB
  • 10. Word2Vec Analysis/4. Training the Word2Vec Model.srt 3.6 kB
  • 7. Project 1 - Text Classification/7. Transform BOW model into TF-IDF Model.vtt 3.4 kB
  • 6. NLP Core/9. POS Tag Meanings.html 3.4 kB
  • 10. Word2Vec Analysis/4. Training the Word2Vec Model.vtt 3.1 kB
  • 8. Project 2 - Twitter Sentiment Analysis/5. Loading TF-IDF Model and Classifier.srt 2.6 kB
  • 7. Project 1 - Text Classification/10. Training our classifier.srt 2.4 kB
  • 8. Project 2 - Twitter Sentiment Analysis/7. Predicting sentiments of tweets.srt 2.3 kB
  • 8. Project 2 - Twitter Sentiment Analysis/5. Loading TF-IDF Model and Classifier.vtt 2.3 kB
  • 1. Introduction to the Course/2. Getting the Course Resources.srt 2.1 kB
  • 7. Project 1 - Text Classification/10. Training our classifier.vtt 2.1 kB
  • 8. Project 2 - Twitter Sentiment Analysis/7. Predicting sentiments of tweets.vtt 2.1 kB
  • 1. Introduction to the Course/2. Getting the Course Resources.vtt 1.9 kB
  • 2. Getting the required softwares/4. How to take this course.html 1.7 kB
  • 6. NLP Core/3. How tokenization works - Text.html 1.6 kB
  • 4. Regular Expressions/6. Character Ranges - Text.html 1.2 kB
  • free-course-site.com-udemy-hands-on-natural-language-processing-nlp-using-python_meta.xml 868 Bytes
  • 7. Project 1 - Text Classification/2. Getting the data for Text Classification - Text.html 806 Bytes
  • 2. Getting the required softwares/2. Installing Anaconda Python - Text.html 734 Bytes
  • 11. Conclusion/1. Where you go from here.html 727 Bytes
  • 1. Introduction to the Course/3. Getting the Course Resources - Text.html 614 Bytes
  • 3. Python Crash Course/12. Test Your Skills.html 156 Bytes
  • 4. Regular Expressions/8. Test Your Skills.html 156 Bytes
  • [FCS Forum].url 133 Bytes
  • [FreeCourseSite.com].url 127 Bytes
  • [CourseClub.NET].url 123 Bytes

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！
>