Text Mining and NLP using R and Python
- 3.2
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Brief Introduction
Data Science Text Mining and NLP using R and PythonDescription
During this course you will be introduced to one of the most important and fast catching up data mining concept. The need for making sense of unstructured data and the knowledge of the various tools is of paramount importance.
Text mining is the first step in data mining of unstructured data.
As part of this course you will be introduced to the various stages of text mining
Understand about word cloud, clustering, and making analysis based on context,
Use of Negative and positive words banks for relational analysis
Work with a live example of extraction of data from Web and perform all the facets of text mining using R and Python
Learn Web and Social media extraction using R, Risk sensing - sentiment analysis, Twitter application management for extracting tweets
Requirements
- Requirements
- Download R & RStudio before starting this tutorial
- Download datasets folder in zipfile which is uploaded in session 1
- While it is not an essential prerequisite, it will be a good idea to go through our course on “Data Mining – Clustering Segmentation Using R, Tableau before going through this course
ExcelR Solutions
3.2 Raiting
Machine Learning and Data Science Hands-on with Python and R
- 3.9
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Machine Learning, Statistics, Python, AI, Tensorflow, AWS, Deep Learning, R Programming, NLP, Bayesian, BI and much more Learn by doing. Full Lifetime Access....
U&P AI - Natural Language Processing (NLP) with Python
- 4.3
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Become an NLP Engineer by creating real projects using Python, semantic search, text mining and search engines! -- UPDATED -- (NEW LESSONS ARE NOT IN THE PROMO VIDEO)...
Natural Language Processing and Text Mining Without Coding
- 4.4
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Analyze Text using Natural Language Processing ( NLP ) techniques & Text Mining without writing a single line of code. Looking to Earn a 6-Figure Income?...
Social Media Data Analytics
- 4.1
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Learner Outcomes: After taking this course, you will be able to: - Analyze unstructured data - primarily textual comments - for sentiments expressed in them....
