Text Analysis and Natural Language Processing With Python

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[ FreeCourseWeb.com ] Udemy - Text Analysis and Natural Language Processing With Python
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 01 Introduction To Social Media Mining With Python
    • 001 Welcome to the Course.en.srt (3.9 KB)
    • 001 Welcome to the Course.mp4 (30.0 MB)
    • 002 Data and Code.html (1.6 KB)
    • 003 Python Installation.en.srt (6.8 KB)
    • 003 Python Installation.mp4 (39.3 MB)
    • 004 What Is Google CoLab_.en.srt (7.8 KB)
    • 004 What Is Google CoLab_.mp4 (36.7 MB)
    • 005 Google Colabs and GPU.en.srt (7.1 KB)
    • 005 Google Colabs and GPU.mp4 (27.6 MB)
    • 006 Google Colab Packages.en.srt (5.1 KB)
    • 006 Google Colab Packages.mp4 (26.5 MB)
    02 Basic Data Preprocessing
    • 001 What Is Pandas_.en.srt (11.6 KB)
    • 001 What Is Pandas_.mp4 (69.7 MB)
    • 002 Basic Data Cleaning With Pandas.en.srt (4.7 KB)
    • 002 Basic Data Cleaning With Pandas.mp4 (31.8 MB)
    • 003 Basics of Data Visualization.en.srt (8.3 KB)
    • 003 Basics of Data Visualization.mp4 (94.1 MB)
    03 Welcome To Social Media
    • 001 Can Social Media Be Useful__ The Case of Twitter.en.srt (5.0 KB)
    • 001 Can Social Media Be Useful__ The Case of Twitter.mp4 (26.7 MB)
    04 Extracting Tweets (Without An API)
    • 001 Obtaining Tweets Without A Twitter Account.en.srt (2.4 KB)
    • 001 Obtaining Tweets Without A Twitter Account.mp4 (27.4 MB)
    • 002 Lets Dip Our Toes Into Twitter.en.srt (1.3 KB)
    • 002 Lets Dip Our Toes Into Twitter.mp4 (8.6 MB)
    • 003 Get Elon Musk's Tweet.en.srt (2.6 KB)
    • 003 Get Elon Musk's Tweet.mp4 (22.2 MB)
    • 004 Obtain The Most Popular Tweets of a User.en.srt (5.6 KB)
    • 004 Obtain The Most Popular Tweets of a User.mp4 (44.9 MB)
    • 005 Obtain Tweets For A User Between A Certain Date.en.srt (4.0 KB)
    • 005 Obtain Tweets For A User Between A Certain Date.mp4 (31.4 MB)
    • 006 Look With For With a Specific Term.en.srt (2.8 KB)
    • 006 Look With For With a Specific Term.mp4 (26.8 MB)
    • 007 Elon Musk's Bitcoin Tweets.en.srt (1.4 KB)
    • 007 Elon Musk's Bitcoin Tweets.mp4 (10.7 MB)
    • 008 Tweets From a Location.en.srt (2.3 KB)
    • 008 Tweets From a Location.mp4 (19.3 MB)
    • 009 Tweets From Multiple Locations.en.srt (3.1 KB)
    • 009 Tweets From Multiple Locations.mp4 (19.6 MB)
    • 010 Tweets From Multiple Locations and Multiple Terms.en.srt (6.9 KB)
    • 010 Tweets From Multiple Locations and Multiple Terms.mp4 (50.0 MB)
    • 011 Another Way of Obtaining Tweets.en.srt (4.1 KB)
    • 011 Another Way of Obtaining Tweets.mp4 (33.7 MB)
    • 012 More Snscrape Tweets.en.srt (3.5 KB)
    • 012 More Snscrape Tweets.mp4 (26.7 MB)
    05 Other Ways of Obtaining Textual Data
    • 001 What is API_.en.srt (3.3 KB)
    • 001 What is API_.mp4 (18.0 MB)
    • 002 Using APIs_ Singapore MRT Stations.en.srt (3.5 KB)
    • 002 Using APIs_ Singapore MRT Stations.mp4 (28.8 MB)
    • 003 Obtain Financial News Headlines.en.srt (4.7 KB)
    • 003 Obtain Financial News Headlines.mp4 (39.7 MB)
    • 004 Obtaining Textual Data From Reddit.en.srt (10.1 KB)
    • 004 Obtaining Textual Data From Reddit.mp4 (80.9 MB)
    06 Basic Textual Data Preprocessing
    • 001 Introduction to Theory.en.srt (5.7 KB)
    • 001 Introduction to Theory.mp4 (58.3 MB)
    • 002 Lets Start Cleaning The Text.en.srt (3.9 KB)
    • 002 Lets Start Cleaning The Text.mp4 (24.2 MB)
    • 003 Final Cleaned Text.en.srt (4.1 KB)
    • 003 Final Cleaned Text.mp4 (27.1 MB)
    • 004 A Function For Text Cleaning.en.srt (3.5 KB)
    • 004 A Function For Text Cleaning.mp4 (37.1 MB)
    • 005 More Text Cleaning.en.srt (3.0 KB)
    • 005 More Text Cleaning.mp4 (26.6 MB)
    • 006 NTLK Cleaning.en.vtt (0.0 KB)
    • 006 NTLK Cleaning.mp4 (34.7 MB)
    • 007 Another NTLK-Based Workflow.en.srt (4.3 KB)
    • 007 Another NTLK-Based Workflow.mp4 (39.0 MB)
    07 Exploring Text Data
    • 001 Tweet Lengths.en.srt (5.3 KB)
    • 001 Tweet Lengths.mp4 (25.6 MB)
    • 002 How People Interact With Tweets.en.srt (2.1 KB)
    • 002 How People Interact With Tweets.mp4 (16.2 MB)
    • 003 Of Mentions and Hashtags.en.srt (2.9 KB)
    • 003 Of Mentions and Hashtags.mp4 (25.7 MB)
    • 004 Identify The Most Popular Hashtags.en.srt (2.5 KB)
    • 004 Identify The Most Popular Hashtags.mp4 (22.4 MB)
    • 005 Identify the Most Common Usernames.en.srt (2.5 KB)
    • 005 Identify the Most Common Usernames.mp4 (11.3 MB)
    • 006 What Are Wordclouds_.en.srt (4.0 KB)
    • 006 What Are Wordclouds_.mp4 (53.0 MB)
    • 007 Basic Wordcloud-Install.en.srt (3.3 KB)
    • 007 Basic Wordcloud-Install.mp4 (21.4 MB)
    • 008 A Basic Wordcloud.en.srt (5.6 KB)
    • 008 A Basic Wordcloud.mp4 (41.5 MB)
    • 009 Word Count of Common Words.en.srt (5.6 KB)
    • 009 Word Count of Common Words.mp4 (41.5 MB)
    • 010 N-Grams.en.srt (5.2 KB)
    • 010 N-Grams.mp4 (27.6 MB)
    • 011 Network of Bigrams.en.srt (4.0 KB)
    • 011 Network of Bigrams.mp4 (22.1 MB)
    • 012 Topic Modelling With Gensim.en.srt (6.8 KB)
    • 012 Topic Modelling With Gensim.mp4 (57.1 MB)
    08 Exploring Sentiments
    • 001 Identify the Polarity of Text.en.srt (5.3 KB)
    • 001 Identify the Polarity of Text.mp4 (43.6 MB)
    • 002 Polarity_ Positive or Negative.en.srt (3.3 KB)
    • 002 Polarity_ Positive or Negative.mp4 (32.0 MB)
    • 003 Dealing With Dates.en.srt (3.9 KB)
    • 003 Dealing With Dates.mp4 (36.1 MB)
    • 004 Introduction to VADER Sentiment Analysis.en.srt (3.0 KB)
    • 004 Introduction to VADER Sentiment Analysis.mp4 (24.3 MB)
    • 005 VADER Sentiment Analysis For Text Analysis.en.srt (4.1 KB)
    • 005 VADER Sentiment Analysis For Text Analysis.mp4 (37.7 MB)
    • 006 VADER Sentiment For Financial News.en.srt (4.8 KB)
    • 006 VADER Sentiment For Financial News.mp4 (38.9 MB)
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Description

Text Analysis and Natural Language Processing With Python

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 67 lectures (4h 36m) | Size: 2.21 GB
Use Python and Google CoLab For Social Media Mining and Text Analysis and Natural Language Processing (NLP)
What you'll learn:
Students will be able to read in data from different sources- including websites and social media
Social media mining from Twitter
Extract information relating to tweets and posts
Analyze text data for emotions
Carry out Sentiment analysis
Implement natural language processing (NLP) on different types of text data
Introduction to some of the most common Python text analysis packages

Requirements
Should have prior experience of Python data science
Prior experience of statistical and machine learning techniques will be beneficial
Should have an interest in extracting unstructured text data from social media and websites
Should have an interest in extracting qinsights from text analysis
Should have an interest in applying machine learning models on text data

Description
ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT PYTHON SOCIAL MEDIA & NATURAL LANGUAGE PROCESSING (NLP)

Do you want to harness the power of social media to make financial decisions?

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Text Analysis and Natural Language Processing With Python


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Text Analysis and Natural Language Processing With Python


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