Natural Language Processing and Statistical Learning notes from Texas A&M University's CSCE 489: Special Topics in Data Mining in Social Networks taught by guest lecturer Dr. Eduardo Nakamura of Brazil.
Here we go! I've officially started work on this book/language as well.
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(0) Section : Simple notes on simple applications in R
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Chapter 1 ISLR : Omitted, as it's an introduction to the book's layout.
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Chapter 2 ISLR : The chapter 2 code-along R exercise in Introduction to Statistical Learning.
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Chapter 2 ISLR Assignment: The chapter 2 assignment after the code-along introduction to R.
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Chapter 3 ISLR : Linear and Multiple Regression
- Supporting Article: http://www.statisticssolutions.com/data-analysis-plan-linear-regression/
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Chapter 4 ISLR : Logistic Regression, LDA, QDA, KNN
- Supporting Article: (LR) https://www.medcalc.org/manual/logistic_regression.php
- Supporting Article: (LDA) http://courses.cs.tamu.edu/rgutier/csce666_f13/mika1999kernelLDA.pdf
- Supporting Article: (QDA) http://www.jmlr.org/papers/volume8/srivastava07a/srivastava07a.pdf
- Supporting Article: (KNN) https://papers.nips.cc/paper/6373-k-nearest-neighbors-from-global-to-local.pdf
- Supporting Article: (K-means) http://www.cs.utexas.edu/users/inderjit/public_papers/neo_kmeans_sdm15.pdf
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Chapter 5 ISLR : Resampling Methods
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Chapter 9 ISLR : Support Vector Machines
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Chapter 9 Homework : A survey of utilizing different kernels in Support Vector Machines
- Supporting publication: https://lirias.kuleuven.be/bitstream/123456789/218716/2/Suykens_NeurProcLett.pdf
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Tidy R : A Tidy approach at text analysis using R
- Supporting book: https://www.tidytextmining.com/
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Sentiment Analysis : An R approach to analyzing sentiment in a text corpus
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TF-IDF : An R approach to Term Frequency - Inverse Document Frequency analysis
- Supporting publication: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.121.1424&rep=rep1&type=pdf