Data Science:Data Mining & Natural Language Processing in R

Harness the Power of Machine Learning in R for Data/Text Mining, & Natural Language Processing with Practical Examples

4.42 (432 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Perform the most important pre-processing tasks needed prior to machine learning in R

Carry out data visualization in R

Use machine learning for unsupervised classification in R

Carry out supervised learning by building classification and regression models in R

Evaluate the accuracy of supervised machine learning algorithms and compare their performance in R

Carry out sentiment analysis using text data in R

Course Gallery

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Data Science:Data Mining & Natural Language Processing in R – Screenshot 3 — Screenshot 3 – Data Science:Data Mining & Natural Language Processing in R

Data Science:Data Mining & Natural Language Processing in R – Screenshot 4 — Screenshot 4 – Data Science:Data Mining & Natural Language Processing in R

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Comidoc Review

Our Verdict

This R Programming course for Data Science enthusiasts is a solid choice with its comprehensive coverage of critical concepts and practical examples. However, the course falls short in providing adequate practice opportunities and clear explanations for some functions used in the demonstrations. Nonetheless, if you're looking to build a foundation in R programming for data science, this course can still be a valuable starting point.

What We Liked

Comprehensive coverage of data analytics and machine learning concepts in R
Practical examples that demonstrate real-world applications
Clear explanation of regression concepts with real-world examples
Well-organized course structure that caters to all levels of participants
Effective use of practical exercises and quizzes for skill reinforcement

Potential Drawbacks

Inadequate emphasis on code implementation best practices
Lack of real-world case studies for practice and application
Some instructions shown in the videos are outdated or do not work as shown
Insufficient explanation of functions, methods, and their intuitions