{ "id": 114724, "title": "19 Great Articles About Natural Language Processing (NLP)", "url": "/competitions/tensorflow2-question-answering/discussion/114724", "author_name": "Tarek Hamdi", "post_date": "2019-10-28T23:01:20.138000", "votes": 106, "comment_count": 74, "views": 0, "content": "

\"\"

\n\n

19 Great Articles About Natural Language Processing (NLP):

\n\n
    \n

  1. Structuring Unstructured Big Data via Indexation

    2. \n

  2. Your Guide to Natural Language Processing (NLP)

    3. \n

  3. Comparison of Top 6 Python NLP Libraries

    4. \n

  4. Text Classification & Sentiment Analysis tutorial

    5. \n

  5. Deep Learning Research Review: Natural Language Processing

    6. \n

  6. 10 Common NLP Terms Explained for the Text Analysis Novice

    7. \n

  7. Temporal Convolutional Nets Take Over from RNNs for NLP Predictions

    8. \n

  8. How I used NLP (Spacy) to screen Data Science Resumes

    9. \n

  9. Data Science Reveals Trump Tweets are Written by Two People

    10. \n

  10. Simple introduction to Natural Language Processing

    11. \n

  11. An NLP Approach to Analyzing Twitter, Trump, and Profanity

    12. \n

  12. A Natural Language Processing (NLP) Approach to Data Exploration

    13. \n

  13. Python NLTK Tools List for Natural Language Processing

    14. \n

  14. NLP app to find great available domain names

    15. \n

  15. Scaling an NLP problem without using a ton of hardware

    16. \n

  16. Analyzing the structure and effectiveness of news headlines

    17. \n

  17. Seven tricky sentences for NLP and text mining algorithms

    18. \n

  18. Overview of Artificial Intelligence and Role of NLP

    19. \n

  19. Text Classification & Sentiment Analysis tutorial

    20. \n
", "messages": [ { "id": 660231, "postDate": "2019-10-28T23:01:20.140Z", "content": "

\"\"

\n\n

19 Great Articles About Natural Language Processing (NLP):

\n\n
    \n

  1. Structuring Unstructured Big Data via Indexation

    2. \n

  2. Your Guide to Natural Language Processing (NLP)

    3. \n

  3. Comparison of Top 6 Python NLP Libraries

    4. \n

  4. Text Classification & Sentiment Analysis tutorial

    5. \n

  5. Deep Learning Research Review: Natural Language Processing

    6. \n

  6. 10 Common NLP Terms Explained for the Text Analysis Novice

    7. \n

  7. Temporal Convolutional Nets Take Over from RNNs for NLP Predictions

    8. \n

  8. How I used NLP (Spacy) to screen Data Science Resumes

    9. \n

  9. Data Science Reveals Trump Tweets are Written by Two People

    10. \n

  10. Simple introduction to Natural Language Processing

    11. \n

  11. An NLP Approach to Analyzing Twitter, Trump, and Profanity

    12. \n

  12. A Natural Language Processing (NLP) Approach to Data Exploration

    13. \n

  13. Python NLTK Tools List for Natural Language Processing

    14. \n

  14. NLP app to find great available domain names

    15. \n

  15. Scaling an NLP problem without using a ton of hardware

    16. \n

  16. Analyzing the structure and effectiveness of news headlines

    17. \n

  17. Seven tricky sentences for NLP and text mining algorithms

    18. \n

  18. Overview of Artificial Intelligence and Role of NLP

    19. \n

  19. Text Classification & Sentiment Analysis tutorial

    20. \n
", "rawMarkdown": "![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fd53f90c89ec69f4fa2b29ad3a1a056e3%2Fnlp.jpg?generation=1572978448691319&alt=media)\n\n**19 Great Articles About Natural Language Processing (NLP):**\n\n1. [Structuring Unstructured Big Data via Indexation](https://www.datasciencecentral.com/profiles/blogs/5-easy-steps-to-structure-highly-unstructured-big-data)\n\n2. [Your Guide to Natural Language Processing (NLP)](https://www.datasciencecentral.com/profiles/blogs/your-guide-to-natural-language-processing-nlp)\n\n3. [Comparison of Top 6 Python NLP Libraries](https://www.datasciencecentral.com/profiles/blogs/comparison-of-top-6-python-nlp-libraries)\n\n4. [Text Classification & Sentiment Analysis tutorial](https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog)\n\n5. [Deep Learning Research Review: Natural Language Processing](https://www.datasciencecentral.com/profiles/blogs/deep-learning-research-review-week-3-natural-language-processing)\n\n6. [10 Common NLP Terms Explained for the Text Analysis Novice](https://www.datasciencecentral.com/profiles/blogs/10-common-nlp-terms-explained-for-the-text-analysis-novice)\n\n7. [Temporal Convolutional Nets Take Over from RNNs for NLP Predictions](https://www.datasciencecentral.com/profiles/blogs/temporal-convolutional-nets-tcns-take-over-from-rnns-for-nlp-pred)\n\n8. [How I used NLP (Spacy) to screen Data Science Resumes](https://www.datasciencecentral.com/profiles/blogs/how-i-used-nlp-spacy-to-screen-data-science-resumes)\n\n9. [Data Science Reveals Trump Tweets are Written by Two People](https://www.datasciencecentral.com/profiles/blogs/data-science-reveals-trump-tweets-are-written-by-two-people)\n\n10. [Simple introduction to Natural Language Processing ](https://www.datasciencecentral.com/profiles/blogs/see-this-simple-introduction-to-natural-language-processing-nlp)\n\n11. [An NLP Approach to Analyzing Twitter, Trump, and Profanity](https://www.datasciencecentral.com/profiles/blogs/an-nlp-approach-to-analyzing-twitter-trump-and-profanity) \n\n12. [A Natural Language Processing (NLP) Approach to Data Exploration](https://www.datasciencecentral.com/video/a-natural-language-processing-nlp-approach-to-data-exploration) \n\n13. [Python NLTK Tools List for Natural Language Processing](https://www.datasciencecentral.com/profiles/blogs/python-nlp-tools) \n\n14. [NLP app to find great available domain names](https://www.datasciencecentral.com/forum/topics/nlp-app-to-find-great-available-domain-names) \n\n15. [Scaling an NLP problem without using a ton of hardware](https://www.datasciencecentral.com/profiles/blogs/short-story-on-scaling-an-nlp-problem-without-using-a-ton-of)\n\n16. [Analyzing the structure and effectiveness of news headlines](https://www.datasciencecentral.com/profiles/blogs/analyzing-the-structure-and-effectiveness-of-news-headlines-using) \n\n17. [Seven tricky sentences for NLP and text mining algorithms](https://www.datasciencecentral.com/profiles/blogs/seven-tricky-sentences-for-nlp-and-text-mining-algorithms) \n\n18. [Overview of Artificial Intelligence and Role of NLP](https://www.datasciencecentral.com/profiles/blogs/overview-of-artificial-intelligence-and-role-of-natural-language) \n\n19. [Text Classification & Sentiment Analysis tutorial](https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog) ", "votes": 105 }, { "id": 2012660, "postDate": "2022-11-01T10:32:19.753Z", "content": "

Cool. It is very helpful!! +1

", "rawMarkdown": "Cool. It is very helpful!! +1", "votes": 1 }, { "id": 1169409, "postDate": "2021-01-25T13:39:20.080Z", "content": "

Very helpful. +1

", "rawMarkdown": "Very helpful. +1", "votes": 1 }, { "id": 1093166, "postDate": "2020-11-27T14:02:19.773Z", "content": "
\n

\"\"

\n

19 Great Articles About Natural Language Processing (NLP):

\n
    \n

  1. Structuring Unstructured Big Data via Indexation

    2. \n

  2. Your Guide to Natural Language Processing (NLP)

    3. \n

  3. Comparison of Top 6 Python NLP Libraries

    4. \n

  4. Text Classification & Sentiment Analysis tutorial

    5. \n

  5. Deep Learning Research Review: Natural Language Processing

    6. \n

  6. 10 Common NLP Terms Explained for the Text Analysis Novice

    7. \n

  7. Temporal Convolutional Nets Take Over from RNNs for NLP Predictions

    8. \n

  8. How I used NLP (Spacy) to screen Data Science Resumes

    9. \n

  9. Data Science Reveals Trump Tweets are Written by Two People

    10. \n

  10. Simple introduction to Natural Language Processing

    11. \n

  11. An NLP Approach to Analyzing Twitter, Trump, and Profanity

    12. \n

  12. A Natural Language Processing (NLP) Approach to Data Exploration

    13. \n

  13. Python NLTK Tools List for Natural Language Processing

    14. \n

  14. NLP app to find great available domain names

    15. \n

  15. Scaling an NLP problem without using a ton of hardware

    16. \n

  16. Analyzing the structure and effectiveness of news headlines

    17. \n

  17. Seven tricky sentences for NLP and text mining algorithms

    18. \n

  18. Overview of Artificial Intelligence and Role of NLP

    19. \n

  19. Text Classification & Sentiment Analysis tutorial

    20. \n
\n
", "rawMarkdown": "> ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fd53f90c89ec69f4fa2b29ad3a1a056e3%2Fnlp.jpg?generation=1572978448691319&alt=media)\n> \n> **19 Great Articles About Natural Language Processing (NLP):**\n> \n> 1. [Structuring Unstructured Big Data via Indexation](https://www.datasciencecentral.com/profiles/blogs/5-easy-steps-to-structure-highly-unstructured-big-data)\n> \n> 2. [Your Guide to Natural Language Processing (NLP)](https://www.datasciencecentral.com/profiles/blogs/your-guide-to-natural-language-processing-nlp)\n> \n> 3. [Comparison of Top 6 Python NLP Libraries](https://www.datasciencecentral.com/profiles/blogs/comparison-of-top-6-python-nlp-libraries)\n> \n> 4. [Text Classification & Sentiment Analysis tutorial](https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog)\n> \n> 5. [Deep Learning Research Review: Natural Language Processing](https://www.datasciencecentral.com/profiles/blogs/deep-learning-research-review-week-3-natural-language-processing)\n> \n> 6. [10 Common NLP Terms Explained for the Text Analysis Novice](https://www.datasciencecentral.com/profiles/blogs/10-common-nlp-terms-explained-for-the-text-analysis-novice)\n> \n> 7. [Temporal Convolutional Nets Take Over from RNNs for NLP Predictions](https://www.datasciencecentral.com/profiles/blogs/temporal-convolutional-nets-tcns-take-over-from-rnns-for-nlp-pred)\n> \n> 8. [How I used NLP (Spacy) to screen Data Science Resumes](https://www.datasciencecentral.com/profiles/blogs/how-i-used-nlp-spacy-to-screen-data-science-resumes)\n> \n> 9. [Data Science Reveals Trump Tweets are Written by Two People](https://www.datasciencecentral.com/profiles/blogs/data-science-reveals-trump-tweets-are-written-by-two-people)\n> \n> 10. [Simple introduction to Natural Language Processing ](https://www.datasciencecentral.com/profiles/blogs/see-this-simple-introduction-to-natural-language-processing-nlp)\n> \n> 11. [An NLP Approach to Analyzing Twitter, Trump, and Profanity](https://www.datasciencecentral.com/profiles/blogs/an-nlp-approach-to-analyzing-twitter-trump-and-profanity) \n> \n> 12. [A Natural Language Processing (NLP) Approach to Data Exploration](https://www.datasciencecentral.com/video/a-natural-language-processing-nlp-approach-to-data-exploration) \n> \n> 13. [Python NLTK Tools List for Natural Language Processing](https://www.datasciencecentral.com/profiles/blogs/python-nlp-tools) \n> \n> 14. [NLP app to find great available domain names](https://www.datasciencecentral.com/forum/topics/nlp-app-to-find-great-available-domain-names) \n> \n> 15. [Scaling an NLP problem without using a ton of hardware](https://www.datasciencecentral.com/profiles/blogs/short-story-on-scaling-an-nlp-problem-without-using-a-ton-of)\n> \n> 16. [Analyzing the structure and effectiveness of news headlines](https://www.datasciencecentral.com/profiles/blogs/analyzing-the-structure-and-effectiveness-of-news-headlines-using) \n> \n> 17. [Seven tricky sentences for NLP and text mining algorithms](https://www.datasciencecentral.com/profiles/blogs/seven-tricky-sentences-for-nlp-and-text-mining-algorithms) \n> \n> 18. [Overview of Artificial Intelligence and Role of NLP](https://www.datasciencecentral.com/profiles/blogs/overview-of-artificial-intelligence-and-role-of-natural-language) \n> \n> 19. [Text Classification & Sentiment Analysis tutorial](https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog)\n\n", "votes": 2 }, { "id": 887821, "postDate": "2020-06-15T22:58:00.623Z", "content": "

This is awesome!

", "rawMarkdown": "This is awesome!", "votes": 1 }, { "id": 716479, "postDate": "2020-01-11T18:58:09.577Z", "content": "

Thanks for sharing !

", "rawMarkdown": "Thanks for sharing ! ", "votes": 1, "replies": [ { "id": 719501, "postDate": "2020-01-15T15:00:03.433Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 1 } ] }, { "id": 713677, "postDate": "2020-01-08T14:40:01.300Z", "content": "

Thanks for the links!

", "rawMarkdown": "Thanks for the links!", "votes": 1, "replies": [ { "id": 719504, "postDate": "2020-01-15T15:00:22.090Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome" } ] }, { "id": 706789, "postDate": "2019-12-30T20:28:15.773Z", "content": "

Very useful to me! Thanks for sharing!!πŸ˜„ πŸ‘

", "rawMarkdown": "Very useful to me! Thanks for sharing!!πŸ˜„ πŸ‘ ", "votes": 1, "replies": [ { "id": 706807, "postDate": "2019-12-30T20:57:37.283Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": -1 } ] }, { "id": 696810, "postDate": "2019-12-17T05:07:16.903Z", "content": "

Nice:)

", "rawMarkdown": "Nice:)", "votes": 1 }, { "id": 696691, "postDate": "2019-12-17T00:28:09.277Z", "content": "

Thank you very much!

", "rawMarkdown": "Thank you very much! ", "votes": 1, "replies": [ { "id": 698096, "postDate": "2019-12-18T19:48:54.643Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome" } ] }, { "id": 695017, "postDate": "2019-12-14T12:57:55.027Z", "content": "

thanks

", "rawMarkdown": "thanks", "votes": 1, "replies": [ { "id": 696644, "postDate": "2019-12-16T21:56:02.787Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome" } ] }, { "id": 691287, "postDate": "2019-12-09T23:21:00.377Z", "content": "

Thanks a lot! Upvoted.

", "rawMarkdown": "Thanks a lot! Upvoted.", "votes": 1, "replies": [ { "id": 692489, "postDate": "2019-12-11T10:22:12.687Z", "content": "

Thanks

", "rawMarkdown": "Thanks", "votes": 1 } ] }, { "id": 682297, "postDate": "2019-11-27T07:54:31.713Z", "content": "

Thanks for this articles, it realy helps!

", "rawMarkdown": "Thanks for this articles, it realy helps!", "votes": 1, "replies": [ { "id": 684244, "postDate": "2019-11-29T13:17:59.703Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome" } ] }, { "id": 681210, "postDate": "2019-11-25T20:56:33.900Z", "content": "

A Comprehensive Guide to Understand and Implement Text Classification in Python

\n\n

https://www.analyticsvidhya.com/blog/2018/04/a-comprehensive-guide-to-understand-and-implement-text-classification-in-python/

", "rawMarkdown": "A Comprehensive Guide to Understand and Implement Text Classification in Python\n\nhttps://www.analyticsvidhya.com/blog/2018/04/a-comprehensive-guide-to-understand-and-implement-text-classification-in-python/", "votes": 1, "replies": [ { "id": 684245, "postDate": "2019-11-29T13:18:17.920Z", "content": "

Thanks

", "rawMarkdown": "Thanks" } ] }, { "id": 681209, "postDate": "2019-11-25T20:55:25.440Z", "content": "

Language Modelling and Text Generation using LSTMs β€” Deep Learning for NLP\nhttps://medium.com/@Zelros/from-bag-of-words-to-transformers-10-years-of-practical-natural-language-processing-8ccc238f679a

", "rawMarkdown": "Language Modelling and Text Generation using LSTMs β€” Deep Learning for NLP\nhttps://medium.com/@Zelros/from-bag-of-words-to-transformers-10-years-of-practical-natural-language-processing-8ccc238f679a", "votes": 1, "replies": [ { "id": 684246, "postDate": "2019-11-29T13:18:25.623Z", "content": "

Thanks

", "rawMarkdown": "Thanks" } ] }, { "id": 681208, "postDate": "2019-11-25T20:53:46.427Z", "content": "

From Bag of Words to Transformers: 10 Years of Practical Natural Language Processing\nhttps://medium.com/@Zelros/from-bag-of-words-to-transformers-10-years-of-practical-natural-language-processing-8ccc238f679a

", "rawMarkdown": "From Bag of Words to Transformers: 10 Years of Practical Natural Language Processing\nhttps://medium.com/@Zelros/from-bag-of-words-to-transformers-10-years-of-practical-natural-language-processing-8ccc238f679a\n", "votes": 1, "replies": [ { "id": 684247, "postDate": "2019-11-29T13:18:33.693Z", "content": "

Thanks

", "rawMarkdown": "Thanks" } ] }, { "id": 679758, "postDate": "2019-11-23T10:32:12.730Z", "content": "

Thank you, that's what i need to start :)

", "rawMarkdown": "Thank you, that's what i need to start :)", "votes": 1, "replies": [ { "id": 680032, "postDate": "2019-11-23T21:53:38.123Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 1 } ] }, { "id": 668781, "postDate": "2019-11-08T20:59:13.383Z", "content": "

Thank you for sharing. This is really helpful

", "rawMarkdown": "Thank you for sharing. This is really helpful", "votes": 1, "replies": [ { "id": 668783, "postDate": "2019-11-08T21:01:24.270Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 3 } ] }, { "id": 667071, "postDate": "2019-11-06T19:29:30.560Z", "content": "

Thanks for sharing!

", "rawMarkdown": "Thanks for sharing!", "votes": 1, "replies": [ { "id": 667540, "postDate": "2019-11-07T10:58:29.893Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 2 } ] }, { "id": 666599, "postDate": "2019-11-06T09:18:29.847Z", "content": "

well done!

", "rawMarkdown": "well done!", "votes": 1, "replies": [ { "id": 667064, "postDate": "2019-11-06T19:15:24.817Z", "content": "

Thx ;)

", "rawMarkdown": "Thx ;)", "votes": 2 } ] }, { "id": 665901, "postDate": "2019-11-05T14:15:07.760Z", "content": "

Awesome, Thank you very much

", "rawMarkdown": "Awesome, Thank you very much", "votes": 1, "replies": [ { "id": 665994, "postDate": "2019-11-05T16:13:11.327Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 2 } ] }, { "id": 665511, "postDate": "2019-11-05T04:18:28.760Z", "content": "

Thanks for sharing! I'll add it to my favorite!πŸ‘Š

", "rawMarkdown": "Thanks for sharing! I'll add it to my favorite!πŸ‘Š ", "votes": 1, "replies": [ { "id": 665839, "postDate": "2019-11-05T13:05:18.893Z", "content": "

Thanks Adrian

", "rawMarkdown": "Thanks Adrian", "votes": 2 } ] }, { "id": 663906, "postDate": "2019-11-02T20:55:32.713Z", "content": "

Nice articles

", "rawMarkdown": "Nice articles", "votes": 1, "replies": [ { "id": 664606, "postDate": "2019-11-04T00:44:10.373Z", "content": "

thanks

", "rawMarkdown": "thanks", "votes": 2 } ] }, { "id": 662210, "postDate": "2019-10-31T08:22:57.580Z", "content": "

It helped me alot. Thank you for the information @hamditarek.

", "rawMarkdown": "It helped me alot. Thank you for the information @hamditarek.", "votes": 1, "replies": [ { "id": 663873, "postDate": "2019-11-02T19:37:59.890Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 2 } ] }, { "id": 661949, "postDate": "2019-10-30T22:43:12.253Z", "content": "

Number 4 and 19 are the same online web-page: https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog

", "rawMarkdown": "Number 4 and 19 are the same online web-page: https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog", "votes": 1, "replies": [ { "id": 663874, "postDate": "2019-11-02T19:38:16.563Z", "content": "

Thanks for sharing

", "rawMarkdown": "Thanks for sharing", "votes": 2 } ] }, { "id": 661644, "postDate": "2019-10-30T14:45:08.387Z", "content": "

Great Collection

", "rawMarkdown": "Great Collection", "votes": 1, "replies": [ { "id": 661648, "postDate": "2019-10-30T14:49:05.320Z", "content": "

Thanks

", "rawMarkdown": "Thanks", "votes": 2 } ] }, { "id": 661540, "postDate": "2019-10-30T12:53:11.260Z", "content": "

Well done! \nThx bro!

", "rawMarkdown": "Well done! \nThx bro!", "votes": 1, "replies": [ { "id": 661585, "postDate": "2019-10-30T13:35:40.897Z", "content": "

You are welcome, good luck

", "rawMarkdown": "You are welcome, good luck", "votes": 2 } ] }, { "id": 661401, "postDate": "2019-10-30T08:50:05.743Z", "content": "

Great collection....thanks for sharing!

", "rawMarkdown": "Great collection....thanks for sharing!", "votes": 1, "replies": [ { "id": 661406, "postDate": "2019-10-30T08:55:55.447Z", "content": "

You are welcome, good luck

", "rawMarkdown": "You are welcome, good luck", "votes": 2 } ] }, { "id": 661104, "postDate": "2019-10-30T00:03:25.320Z", "content": "

Nice, thank you!

", "rawMarkdown": "Nice, thank you!", "votes": 1, "replies": [ { "id": 661269, "postDate": "2019-10-30T04:16:03.510Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 2 } ] }, { "id": 664735, "postDate": "2019-11-04T06:32:29.610Z", "content": "

Very Informative article.Thanks.

", "rawMarkdown": "Very Informative article.Thanks.", "votes": 2, "replies": [ { "id": 665321, "postDate": "2019-11-04T21:52:58.617Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 2 } ] }, { "id": 664693, "postDate": "2019-11-04T04:31:16.720Z", "content": "

Useful articles, thanks for sharing!

", "rawMarkdown": "Useful articles, thanks for sharing!", "votes": 2, "replies": [ { "id": 665322, "postDate": "2019-11-04T21:53:16.843Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 2 } ] }, { "id": 664626, "postDate": "2019-11-04T01:45:36.617Z", "content": "

That's very helpful collection! Thanks.

", "rawMarkdown": "That's very helpful collection! Thanks.", "votes": 2, "replies": [ { "id": 665323, "postDate": "2019-11-04T21:53:37.020Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 2 } ] }, { "id": 662455, "postDate": "2019-10-31T15:22:23.143Z", "content": "

Thanks!

", "rawMarkdown": "Thanks!", "votes": 2, "replies": [ { "id": 663871, "postDate": "2019-11-02T19:37:22.720Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 2 } ] }, { "id": 662230, "postDate": "2019-10-31T09:13:48.760Z", "content": "

This is really helpful. Thanks a ton.

", "rawMarkdown": "This is really helpful. Thanks a ton.", "votes": 2, "replies": [ { "id": 663872, "postDate": "2019-11-02T19:37:38.630Z", "content": "

You are welcome

", "rawMarkdown": "You are welcome", "votes": 2 } ] }, { "id": 660574, "postDate": "2019-10-29T10:57:18.863Z", "content": "

Great Collection\nThanks @hamditarek

", "rawMarkdown": "Great Collection\nThanks @hamditarek ", "votes": 2, "replies": [ { "id": 660584, "postDate": "2019-10-29T11:05:52.987Z", "content": "

You are welcome and good luck

", "rawMarkdown": "You are welcome and good luck", "votes": 2 } ] }, { "id": 660481, "postDate": "2019-10-29T07:41:15.427Z", "content": "

salam

", "rawMarkdown": "salam", "votes": 2, "replies": [ { "id": 660493, "postDate": "2019-10-29T08:06:34.510Z", "content": "

Salam bro,\nwelcome to kaggle

", "rawMarkdown": "Salam bro,\nwelcome to kaggle", "votes": 2 } ] }, { "id": 683854, "postDate": "2019-11-28T22:41:50.530Z", "rawMarkdown": "", "votes": 1, "isDeleted": true, "replies": [ { "id": 684242, "postDate": "2019-11-29T13:17:16.767Z", "content": "

You are welcome @vbabson

", "rawMarkdown": "You are welcome @vbabson " } ] }, { "id": 670076, "postDate": "2019-11-11T00:59:33.080Z", "rawMarkdown": "", "isDeleted": true }, { "id": 661432, "postDate": "2019-10-30T09:34:20.080Z", "rawMarkdown": "", "votes": 2, "isDeleted": true, "replies": [ { "id": 661586, "postDate": "2019-10-30T13:35:53.560Z", "content": "

You are welcome, good luck

", "rawMarkdown": "You are welcome, good luck", "votes": 2 } ] }, { "id": 661383, "postDate": "2019-10-30T08:20:02.813Z", "rawMarkdown": "", "votes": 1, "isDeleted": true, "replies": [ { "id": 661397, "postDate": "2019-10-30T08:44:14.247Z", "content": "

You are welcome.

", "rawMarkdown": "You are welcome.", "votes": 2 } ] }, { "id": 1170352, "postDate": "2021-01-26T06:58:15.247Z", "content": "

Helpful links.. thanks

", "rawMarkdown": "Helpful links.. thanks", "votes": 1 }, { "id": 1009647, "postDate": "2020-09-14T06:45:47.420Z", "content": "

Thanks for sharing the links …

", "rawMarkdown": "Thanks for sharing the links ...", "votes": 1 } ], "comments": [ { "id": 2012660, "author_name": "Olqa_842", "author_url": "", "post_date": "2022-11-01T10:32:19.753000", "content": "

Cool. It is very helpful!! +1

", "votes": 1, "replies": [] }, { "id": 1169409, "author_name": "Krish Yadav", "author_url": "", "post_date": "2021-01-25T13:39:20.080000", "content": "

Very helpful. +1

", "votes": 1, "replies": [] }, { "id": 1093166, "author_name": "Anh Nguyen Q.", "author_url": "", "post_date": "2020-11-27T14:02:19.773000", "content": "
\n

\"\"

\n

19 Great Articles About Natural Language Processing (NLP):

\n
    \n

  1. Structuring Unstructured Big Data via Indexation

    2. \n

  2. Your Guide to Natural Language Processing (NLP)

    3. \n

  3. Comparison of Top 6 Python NLP Libraries

    4. \n

  4. Text Classification & Sentiment Analysis tutorial

    5. \n

  5. Deep Learning Research Review: Natural Language Processing

    6. \n

  6. 10 Common NLP Terms Explained for the Text Analysis Novice

    7. \n

  7. Temporal Convolutional Nets Take Over from RNNs for NLP Predictions

    8. \n

  8. How I used NLP (Spacy) to screen Data Science Resumes

    9. \n

  9. Data Science Reveals Trump Tweets are Written by Two People

    10. \n

  10. Simple introduction to Natural Language Processing

    11. \n

  11. An NLP Approach to Analyzing Twitter, Trump, and Profanity

    12. \n

  12. A Natural Language Processing (NLP) Approach to Data Exploration

    13. \n

  13. Python NLTK Tools List for Natural Language Processing

    14. \n

  14. NLP app to find great available domain names

    15. \n

  15. Scaling an NLP problem without using a ton of hardware

    16. \n

  16. Analyzing the structure and effectiveness of news headlines

    17. \n

  17. Seven tricky sentences for NLP and text mining algorithms

    18. \n

  18. Overview of Artificial Intelligence and Role of NLP

    19. \n

  19. Text Classification & Sentiment Analysis tutorial

    20. \n
\n
", "votes": 2, "replies": [] }, { "id": 887821, "author_name": "Lindsay Wang", "author_url": "", "post_date": "2020-06-15T22:58:00.623000", "content": "

This is awesome!

", "votes": 1, "replies": [] }, { "id": 716479, "author_name": "Sandeep Krishna Donepudi", "author_url": "", "post_date": "2020-01-11T18:58:09.577000", "content": "

Thanks for sharing !

", "votes": 1, "replies": [ { "id": 719501, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-01-15T15:00:03.433000", "content": "

You are welcome

", "votes": 1, "replies": [] } ] }, { "id": 713677, "author_name": "Shrek_fan", "author_url": "", "post_date": "2020-01-08T14:40:01.300000", "content": "

Thanks for the links!

", "votes": 1, "replies": [ { "id": 719504, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2020-01-15T15:00:22.090000", "content": "

You are welcome

", "votes": 0, "replies": [] } ] }, { "id": 706789, "author_name": "Miyabon", "author_url": "", "post_date": "2019-12-30T20:28:15.773000", "content": "

Very useful to me! Thanks for sharing!!πŸ˜„ πŸ‘

", "votes": 1, "replies": [ { "id": 706807, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-12-30T20:57:37.283000", "content": "

You are welcome

", "votes": -1, "replies": [] } ] }, { "id": 696810, "author_name": "Shreyas Chopra", "author_url": "", "post_date": "2019-12-17T05:07:16.903000", "content": "

Nice:)

", "votes": 1, "replies": [] }, { "id": 696691, "author_name": "Stanislav Lykov", "author_url": "", "post_date": "2019-12-17T00:28:09.277000", "content": "

Thank you very much!

", "votes": 1, "replies": [ { "id": 698096, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-12-18T19:48:54.643000", "content": "

You are welcome

", "votes": 0, "replies": [] } ] }, { "id": 695017, "author_name": "baoquoc2021", "author_url": "", "post_date": "2019-12-14T12:57:55.027000", "content": "

thanks

", "votes": 1, "replies": [ { "id": 696644, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-12-16T21:56:02.787000", "content": "

You are welcome

", "votes": 0, "replies": [] } ] }, { "id": 691287, "author_name": "cxue34", "author_url": "", "post_date": "2019-12-09T23:21:00.377000", "content": "

Thanks a lot! Upvoted.

", "votes": 1, "replies": [ { "id": 692489, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-12-11T10:22:12.687000", "content": "

Thanks

", "votes": 1, "replies": [] } ] }, { "id": 682297, "author_name": "Volodymyr Prypeshniuk", "author_url": "", "post_date": "2019-11-27T07:54:31.713000", "content": "

Thanks for this articles, it realy helps!

", "votes": 1, "replies": [ { "id": 684244, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-29T13:17:59.703000", "content": "

You are welcome

", "votes": 0, "replies": [] } ] }, { "id": 681210, "author_name": "Kennedy Kamande Wangari", "author_url": "", "post_date": "2019-11-25T20:56:33.900000", "content": "

A Comprehensive Guide to Understand and Implement Text Classification in Python

\n\n

https://www.analyticsvidhya.com/blog/2018/04/a-comprehensive-guide-to-understand-and-implement-text-classification-in-python/

", "votes": 1, "replies": [ { "id": 684245, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-29T13:18:17.920000", "content": "

Thanks

", "votes": 0, "replies": [] } ] }, { "id": 681209, "author_name": "Kennedy Kamande Wangari", "author_url": "", "post_date": "2019-11-25T20:55:25.440000", "content": "

Language Modelling and Text Generation using LSTMs β€” Deep Learning for NLP\nhttps://medium.com/@Zelros/from-bag-of-words-to-transformers-10-years-of-practical-natural-language-processing-8ccc238f679a

", "votes": 1, "replies": [ { "id": 684246, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-29T13:18:25.623000", "content": "

Thanks

", "votes": 0, "replies": [] } ] }, { "id": 681208, "author_name": "Kennedy Kamande Wangari", "author_url": "", "post_date": "2019-11-25T20:53:46.427000", "content": "

From Bag of Words to Transformers: 10 Years of Practical Natural Language Processing\nhttps://medium.com/@Zelros/from-bag-of-words-to-transformers-10-years-of-practical-natural-language-processing-8ccc238f679a

", "votes": 1, "replies": [ { "id": 684247, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-29T13:18:33.693000", "content": "

Thanks

", "votes": 0, "replies": [] } ] }, { "id": 679758, "author_name": "MichaΕ‚ Razny", "author_url": "", "post_date": "2019-11-23T10:32:12.730000", "content": "

Thank you, that's what i need to start :)

", "votes": 1, "replies": [ { "id": 680032, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-23T21:53:38.123000", "content": "

You are welcome

", "votes": 1, "replies": [] } ] }, { "id": 668781, "author_name": "Marwane97", "author_url": "", "post_date": "2019-11-08T20:59:13.383000", "content": "

Thank you for sharing. This is really helpful

", "votes": 1, "replies": [ { "id": 668783, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-08T21:01:24.270000", "content": "

You are welcome

", "votes": 3, "replies": [] } ] }, { "id": 667071, "author_name": "ChanceGu", "author_url": "", "post_date": "2019-11-06T19:29:30.560000", "content": "

Thanks for sharing!

", "votes": 1, "replies": [ { "id": 667540, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-07T10:58:29.893000", "content": "

You are welcome

", "votes": 2, "replies": [] } ] }, { "id": 666599, "author_name": "Index", "author_url": "", "post_date": "2019-11-06T09:18:29.847000", "content": "

well done!

", "votes": 1, "replies": [ { "id": 667064, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-06T19:15:24.817000", "content": "

Thx ;)

", "votes": 2, "replies": [] } ] }, { "id": 665901, "author_name": "Abhishek Pathak", "author_url": "", "post_date": "2019-11-05T14:15:07.760000", "content": "

Awesome, Thank you very much

", "votes": 1, "replies": [ { "id": 665994, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-05T16:13:11.327000", "content": "

You are welcome

", "votes": 2, "replies": [] } ] }, { "id": 665511, "author_name": "Adrian Zinovei", "author_url": "", "post_date": "2019-11-05T04:18:28.760000", "content": "

Thanks for sharing! I'll add it to my favorite!πŸ‘Š

", "votes": 1, "replies": [ { "id": 665839, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-05T13:05:18.893000", "content": "

Thanks Adrian

", "votes": 2, "replies": [] } ] }, { "id": 663906, "author_name": "SeshuRaju πŸ§˜β€β™‚οΈ", "author_url": "", "post_date": "2019-11-02T20:55:32.713000", "content": "

Nice articles

", "votes": 1, "replies": [ { "id": 664606, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-04T00:44:10.373000", "content": "

thanks

", "votes": 2, "replies": [] } ] }, { "id": 662210, "author_name": "Ashutosh Hathidara", "author_url": "", "post_date": "2019-10-31T08:22:57.580000", "content": "

It helped me alot. Thank you for the information @hamditarek.

", "votes": 1, "replies": [ { "id": 663873, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-02T19:37:59.890000", "content": "

You are welcome

", "votes": 2, "replies": [] } ] }, { "id": 661949, "author_name": "Yauhen", "author_url": "", "post_date": "2019-10-30T22:43:12.253000", "content": "

Number 4 and 19 are the same online web-page: https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog

", "votes": 1, "replies": [ { "id": 663874, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-02T19:38:16.563000", "content": "

Thanks for sharing

", "votes": 2, "replies": [] } ] }, { "id": 661644, "author_name": "Medaminbf", "author_url": "", "post_date": "2019-10-30T14:45:08.387000", "content": "

Great Collection

", "votes": 1, "replies": [ { "id": 661648, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-10-30T14:49:05.320000", "content": "

Thanks

", "votes": 2, "replies": [] } ] }, { "id": 661540, "author_name": "Jimmy_Xu", "author_url": "", "post_date": "2019-10-30T12:53:11.260000", "content": "

Well done! \nThx bro!

", "votes": 1, "replies": [ { "id": 661585, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-10-30T13:35:40.897000", "content": "

You are welcome, good luck

", "votes": 2, "replies": [] } ] }, { "id": 661401, "author_name": "Gaurav kumar", "author_url": "", "post_date": "2019-10-30T08:50:05.743000", "content": "

Great collection....thanks for sharing!

", "votes": 1, "replies": [ { "id": 661406, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-10-30T08:55:55.447000", "content": "

You are welcome, good luck

", "votes": 2, "replies": [] } ] }, { "id": 661104, "author_name": "Jake Farrell", "author_url": "", "post_date": "2019-10-30T00:03:25.320000", "content": "

Nice, thank you!

", "votes": 1, "replies": [ { "id": 661269, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-10-30T04:16:03.510000", "content": "

You are welcome

", "votes": 2, "replies": [] } ] }, { "id": 664735, "author_name": "Sourav Prasad", "author_url": "", "post_date": "2019-11-04T06:32:29.610000", "content": "

Very Informative article.Thanks.

", "votes": 2, "replies": [ { "id": 665321, "author_name": "Tarek Hamdi", "author_url": "", "post_date": "2019-11-04T21:52:58.617000", "content": "

You are welcome

", "votes": 2, "replies": [] } ] }, { "id": 664693, "author_name": "", "author_url": "", "post_date": "2019-11-04T04:31:16.720000", "content": "", "votes": 2, "replies": [ { "id": 665322, "author_name": "", "author_url": "", "post_date": "2019-11-04T21:53:16.843000", "content": "", "votes": 2, "replies": [] } ] }, { "id": 664626, "author_name": "", "author_url": "", "post_date": "2019-11-04T01:45:36.617000", "content": "", "votes": 2, "replies": [ { "id": 665323, "author_name": "", "author_url": "", "post_date": "2019-11-04T21:53:37.020000", "content": "", "votes": 2, "replies": [] } ] }, { "id": 662455, "author_name": "", "author_url": "", "post_date": "2019-10-31T15:22:23.143000", "content": "", "votes": 2, "replies": [ { "id": 663871, "author_name": "", "author_url": "", "post_date": "2019-11-02T19:37:22.720000", "content": "", "votes": 2, "replies": [] } ] }, { "id": 662230, "author_name": "", "author_url": "", "post_date": "2019-10-31T09:13:48.760000", "content": "", "votes": 2, "replies": [ { "id": 663872, "author_name": "", "author_url": "", "post_date": "2019-11-02T19:37:38.630000", "content": "", "votes": 2, "replies": [] } ] }, { "id": 660574, "author_name": "", "author_url": "", "post_date": "2019-10-29T10:57:18.863000", "content": "", "votes": 2, "replies": [ { "id": 660584, "author_name": "", "author_url": "", "post_date": "2019-10-29T11:05:52.987000", "content": "", "votes": 2, "replies": [] } ] }, { "id": 660481, "author_name": "", "author_url": "", "post_date": "2019-10-29T07:41:15.427000", "content": "", "votes": 2, "replies": [ { "id": 660493, "author_name": "", "author_url": "", "post_date": "2019-10-29T08:06:34.510000", "content": "", "votes": 2, "replies": [] } ] }, { "id": 683854, "author_name": "", "author_url": "", "post_date": "2019-11-28T22:41:50.530000", "content": "", "votes": 1, "replies": [ { "id": 684242, "author_name": "", "author_url": "", "post_date": "2019-11-29T13:17:16.767000", "content": "", "votes": 0, "replies": [] } ] }, { "id": 670076, "author_name": "", "author_url": "", "post_date": "2019-11-11T00:59:33.080000", "content": "", "votes": 0, "replies": [] }, { "id": 661432, "author_name": "", "author_url": "", "post_date": "2019-10-30T09:34:20.080000", "content": "", "votes": 2, "replies": [ { "id": 661586, "author_name": "", "author_url": "", "post_date": "2019-10-30T13:35:53.560000", "content": "", "votes": 2, "replies": [] } ] }, { "id": 661383, "author_name": "", "author_url": "", "post_date": "2019-10-30T08:20:02.813000", "content": "", "votes": 1, "replies": [ { "id": 661397, "author_name": "", "author_url": "", "post_date": "2019-10-30T08:44:14.247000", "content": "", "votes": 2, "replies": [] } ] }, { "id": 1170352, "author_name": "", "author_url": "", "post_date": "2021-01-26T06:58:15.247000", "content": "", "votes": 1, "replies": [] }, { "id": 1009647, "author_name": "", "author_url": "", "post_date": "2020-09-14T06:45:47.420000", "content": "", "votes": 1, "replies": [] } ], "raw_markdown_by_id": { "660231": "![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fd53f90c89ec69f4fa2b29ad3a1a056e3%2Fnlp.jpg?generation=1572978448691319&alt=media)\n\n**19 Great Articles About Natural Language Processing (NLP):**\n\n1. [Structuring Unstructured Big Data via Indexation](https://www.datasciencecentral.com/profiles/blogs/5-easy-steps-to-structure-highly-unstructured-big-data)\n\n2. [Your Guide to Natural Language Processing (NLP)](https://www.datasciencecentral.com/profiles/blogs/your-guide-to-natural-language-processing-nlp)\n\n3. [Comparison of Top 6 Python NLP Libraries](https://www.datasciencecentral.com/profiles/blogs/comparison-of-top-6-python-nlp-libraries)\n\n4. [Text Classification & Sentiment Analysis tutorial](https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog)\n\n5. [Deep Learning Research Review: Natural Language Processing](https://www.datasciencecentral.com/profiles/blogs/deep-learning-research-review-week-3-natural-language-processing)\n\n6. [10 Common NLP Terms Explained for the Text Analysis Novice](https://www.datasciencecentral.com/profiles/blogs/10-common-nlp-terms-explained-for-the-text-analysis-novice)\n\n7. [Temporal Convolutional Nets Take Over from RNNs for NLP Predictions](https://www.datasciencecentral.com/profiles/blogs/temporal-convolutional-nets-tcns-take-over-from-rnns-for-nlp-pred)\n\n8. [How I used NLP (Spacy) to screen Data Science Resumes](https://www.datasciencecentral.com/profiles/blogs/how-i-used-nlp-spacy-to-screen-data-science-resumes)\n\n9. [Data Science Reveals Trump Tweets are Written by Two People](https://www.datasciencecentral.com/profiles/blogs/data-science-reveals-trump-tweets-are-written-by-two-people)\n\n10. [Simple introduction to Natural Language Processing ](https://www.datasciencecentral.com/profiles/blogs/see-this-simple-introduction-to-natural-language-processing-nlp)\n\n11. [An NLP Approach to Analyzing Twitter, Trump, and Profanity](https://www.datasciencecentral.com/profiles/blogs/an-nlp-approach-to-analyzing-twitter-trump-and-profanity) \n\n12. [A Natural Language Processing (NLP) Approach to Data Exploration](https://www.datasciencecentral.com/video/a-natural-language-processing-nlp-approach-to-data-exploration) \n\n13. [Python NLTK Tools List for Natural Language Processing](https://www.datasciencecentral.com/profiles/blogs/python-nlp-tools) \n\n14. [NLP app to find great available domain names](https://www.datasciencecentral.com/forum/topics/nlp-app-to-find-great-available-domain-names) \n\n15. [Scaling an NLP problem without using a ton of hardware](https://www.datasciencecentral.com/profiles/blogs/short-story-on-scaling-an-nlp-problem-without-using-a-ton-of)\n\n16. [Analyzing the structure and effectiveness of news headlines](https://www.datasciencecentral.com/profiles/blogs/analyzing-the-structure-and-effectiveness-of-news-headlines-using) \n\n17. [Seven tricky sentences for NLP and text mining algorithms](https://www.datasciencecentral.com/profiles/blogs/seven-tricky-sentences-for-nlp-and-text-mining-algorithms) \n\n18. [Overview of Artificial Intelligence and Role of NLP](https://www.datasciencecentral.com/profiles/blogs/overview-of-artificial-intelligence-and-role-of-natural-language) \n\n19. [Text Classification & Sentiment Analysis tutorial](https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog) ", "2012660": "Cool. It is very helpful!! +1", "1169409": "Very helpful. +1", "1093166": "> ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fd53f90c89ec69f4fa2b29ad3a1a056e3%2Fnlp.jpg?generation=1572978448691319&alt=media)\n> \n> **19 Great Articles About Natural Language Processing (NLP):**\n> \n> 1. [Structuring Unstructured Big Data via Indexation](https://www.datasciencecentral.com/profiles/blogs/5-easy-steps-to-structure-highly-unstructured-big-data)\n> \n> 2. [Your Guide to Natural Language Processing (NLP)](https://www.datasciencecentral.com/profiles/blogs/your-guide-to-natural-language-processing-nlp)\n> \n> 3. [Comparison of Top 6 Python NLP Libraries](https://www.datasciencecentral.com/profiles/blogs/comparison-of-top-6-python-nlp-libraries)\n> \n> 4. [Text Classification & Sentiment Analysis tutorial](https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog)\n> \n> 5. [Deep Learning Research Review: Natural Language Processing](https://www.datasciencecentral.com/profiles/blogs/deep-learning-research-review-week-3-natural-language-processing)\n> \n> 6. [10 Common NLP Terms Explained for the Text Analysis Novice](https://www.datasciencecentral.com/profiles/blogs/10-common-nlp-terms-explained-for-the-text-analysis-novice)\n> \n> 7. [Temporal Convolutional Nets Take Over from RNNs for NLP Predictions](https://www.datasciencecentral.com/profiles/blogs/temporal-convolutional-nets-tcns-take-over-from-rnns-for-nlp-pred)\n> \n> 8. [How I used NLP (Spacy) to screen Data Science Resumes](https://www.datasciencecentral.com/profiles/blogs/how-i-used-nlp-spacy-to-screen-data-science-resumes)\n> \n> 9. [Data Science Reveals Trump Tweets are Written by Two People](https://www.datasciencecentral.com/profiles/blogs/data-science-reveals-trump-tweets-are-written-by-two-people)\n> \n> 10. [Simple introduction to Natural Language Processing ](https://www.datasciencecentral.com/profiles/blogs/see-this-simple-introduction-to-natural-language-processing-nlp)\n> \n> 11. [An NLP Approach to Analyzing Twitter, Trump, and Profanity](https://www.datasciencecentral.com/profiles/blogs/an-nlp-approach-to-analyzing-twitter-trump-and-profanity) \n> \n> 12. [A Natural Language Processing (NLP) Approach to Data Exploration](https://www.datasciencecentral.com/video/a-natural-language-processing-nlp-approach-to-data-exploration) \n> \n> 13. [Python NLTK Tools List for Natural Language Processing](https://www.datasciencecentral.com/profiles/blogs/python-nlp-tools) \n> \n> 14. [NLP app to find great available domain names](https://www.datasciencecentral.com/forum/topics/nlp-app-to-find-great-available-domain-names) \n> \n> 15. [Scaling an NLP problem without using a ton of hardware](https://www.datasciencecentral.com/profiles/blogs/short-story-on-scaling-an-nlp-problem-without-using-a-ton-of)\n> \n> 16. [Analyzing the structure and effectiveness of news headlines](https://www.datasciencecentral.com/profiles/blogs/analyzing-the-structure-and-effectiveness-of-news-headlines-using) \n> \n> 17. [Seven tricky sentences for NLP and text mining algorithms](https://www.datasciencecentral.com/profiles/blogs/seven-tricky-sentences-for-nlp-and-text-mining-algorithms) \n> \n> 18. [Overview of Artificial Intelligence and Role of NLP](https://www.datasciencecentral.com/profiles/blogs/overview-of-artificial-intelligence-and-role-of-natural-language) \n> \n> 19. [Text Classification & Sentiment Analysis tutorial](https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog)\n\n", "887821": "This is awesome!", "716479": "Thanks for sharing ! ", "713677": "Thanks for the links!", "706789": "Very useful to me! Thanks for sharing!!πŸ˜„ πŸ‘ ", "696810": "Nice:)", "696691": "Thank you very much! ", "695017": "thanks", "691287": "Thanks a lot! Upvoted.", "682297": "Thanks for this articles, it realy helps!", "681210": "A Comprehensive Guide to Understand and Implement Text Classification in Python\n\nhttps://www.analyticsvidhya.com/blog/2018/04/a-comprehensive-guide-to-understand-and-implement-text-classification-in-python/", "681209": "Language Modelling and Text Generation using LSTMs β€” Deep Learning for NLP\nhttps://medium.com/@Zelros/from-bag-of-words-to-transformers-10-years-of-practical-natural-language-processing-8ccc238f679a", "681208": "From Bag of Words to Transformers: 10 Years of Practical Natural Language Processing\nhttps://medium.com/@Zelros/from-bag-of-words-to-transformers-10-years-of-practical-natural-language-processing-8ccc238f679a\n", "679758": "Thank you, that's what i need to start :)", "668781": "Thank you for sharing. This is really helpful", "667071": "Thanks for sharing!", "666599": "well done!", "665901": "Awesome, Thank you very much", "665511": "Thanks for sharing! I'll add it to my favorite!πŸ‘Š ", "663906": "Nice articles", "662210": "It helped me alot. Thank you for the information @hamditarek.", "661949": "Number 4 and 19 are the same online web-page: https://www.datasciencecentral.com/profiles/blogs/text-classification-sentiment-analysis-tutorial-blog", "661644": "Great Collection", "661540": "Well done! \nThx bro!", "661401": "Great collection....thanks for sharing!", "661104": "Nice, thank you!", "664735": "Very Informative article.Thanks.", "664693": "Useful articles, thanks for sharing!", "664626": "That's very helpful collection! Thanks.", "662455": "Thanks!", "662230": "This is really helpful. Thanks a ton.", "660574": "Great Collection\nThanks @hamditarek ", "660481": "salam", "683854": "", "670076": "", "661432": "", "661383": "", "1170352": "Helpful links.. thanks", "1009647": "Thanks for sharing the links ..." } }