gravatar

wilsonchua

wilson chua

Recently Published

KEC-Titanic Demo
Predict who is most likely to survive
Knowledge Exchange Conference 2018
Sample R script
Demo of igraph and d3Network
fasdf
RootCon 2017 Extra Codes
Some tips based on the book Data Driven Security
MLR-Section39-XGBoost
XGBoost
MLR-Section38-GridSearch
GridSearch
MLR-Section38 XValidation
x Fold Validation
MLR-Section37-KernelPCA
Kernel PCA
MLR-Section36-LDA
Linear Discriminant Analysis
MLR-Section34 PCA
Principal component analysis
MLR-Section31-ANN
Advanced Neural Networks
MLR-Section28-Thompson Sampling
MLR-section25 UpperConfidenceBoundary
Multi arm bandit
ML in R Hierarchical Clustering
Section21 K Means Clustering
ML using R section 17 Decision Tree
Decision Tree
ML using R Section 16 Naive Bayes
Naïve Bayes
ML Using R Section 15 Kernel SVM
Kernel SVM for non linear dataset
ML Using R Section 14 SVM
Support Vector Machine
ML Using R Section 13 KNN
KNearest Neighbor
ML Using R Section 12
Logistic Regression
ML Using R Section 9
Random Forest
ML Using R Section 8
Decision Tree Regressions
ML Using R Section 7
Support Vector Regression
ML Using R Section 6
Polynomial Regression
ML Using R Section 5
Multiple Linear Regression
ML Using R
Linear Regression
R for Data Science Model Building
Chapter 19
BASS TEST One
R For Data Science- Markdown Output
Chapter 23
R for Data Science R Markdown
Chapter 23
R for Data Science Chapter 18
Introduction to Modeling
R for Data Science Chapter 16 Vectors
Vectors
R4DS Chapter 15 Functions
R for Data Science Chapter 14 Magritter %>%
Library(magrittr) %>% pipes
R For Data Science Chapter 13 Lubridate
All about dates and times
R For Data Science Chapter 12
Factors with forcats package
R For Data Science Chapter 11
Strings with Stringr
R for Data Science Chapter 10
Relational Data with Tidyr
R for Data Science Chapter 09
Tidy Data with Tidyr
R for Data Science Chapter 8
Data Import with readr
R For Data Science Chapter 6 Workflow Projects
Workflow Projects
R For Data Science Chapter 5
Exploratory Data Analysis
R for Data Science Chapter 4
Chapter 4 of R4DS
R for Data Science-Chapter 3
Data Transformation with dplyr
R for Data Science Chapter 2
Workflow: Basics
Chapter 1 R for Data Science
Chapter 15 Elementary Statistics
One of the hardest chapters to follow. I wish the author made it with plain english
Document
test
Chapter 13 Basic Statistics
centrality: mean, median, mode correlations, variance, covariance, standard deviation, summary iqr, quantiles
Chapter 11 Writing Functions
Chapter 10 Conditions and Loops
if, else, ifelse, nesting, stacking,switch, for loops, nesting, while, apply, next, break, repeat
Chapter 9 Writing Functions
Scoping, Matching
Chapter 7 Basic Plotting with R
Chapter 7 of The book of R
Chapter 6
The Book of R chapter 6
Document1
test
The Book of R Chapter 4
Lab for Chapter 4
Lab Notes on "The Book of R"
My lab notes on following the examples in the excellent book "The Book of R" by Tilman Davies
Plot2
ggplotsample2
Plot Test R programming Class
Singapore Jan 2017