## Recently Published

##### Big-ish Data Workflow in R

This article aims to replicate the recently (2015) plotly article in R.
Link to article:
Big data analytics with Pandas and SQLite
Please make comments or suggestions via email, issues, or pull requests.

##### R for Interactive Reporting

Using dygraphs and DT to make interactive reports using R

##### Non-Linear Models

Splines, Local Regression, Polynomial Regression, GAM

##### Support Vector Machines

Using caret and e1071. Start to finish: teaching the concepts to full examples.

##### Resampling Methods

cross validation and bootstrap theory and examples

##### Auto Generate Markdown Tables

use knitr to beautify your table outputs in your reproducible research.

##### Classification1_Examples

KNN, logistic regression, LDA, QDA, random forests examples using the Boston dataset

##### TimeSeriesAnalysis5

More time series analysis:
Seasonal ARIMA models + forecasting.

##### TimeSeriesAnalysis2

Time series Analysis:
Stationarity
Smoothing methods

##### TimeSeriesAnalysis1

Intro to time series analysis

##### TimeSeriesAnalysisExamples

Lots of start-to-finish times series analysis examples. Very informative.

##### TimeSeriesAnalysis4

Forecasting with non-seasonal ARIMA models

##### TimeSeriesAnalysis3

ARIMA models for time series analysis

##### Classification_LDA_QDA

Linear Discriminant Analysis and Quadratic DA in R.

##### Classification: Logistic Regression

Classification: Logistic Regression

##### Start to Finish: Time Series Analysis

A few start to finish examples of time series analysis with ARIMA models

##### Seasonal ARIMA models

Model fitting and forecasting

##### Machine Learning 2

Mostly introduces the `caret` package in R, and how to apply it to solve some machine learning tools

##### Time Series Analysis 4

Introduction to forecasting with non-seasonal ARIMA models

##### Machine Learning: Initial Considerations

Material taken from the coursera class, link inside.

##### Time Series Analysis 3

AR, MA, ARMA, ARIMA models
Diagnostics
Examples

##### Time Series Analysis 2

Stationarity, ACF and CCF

##### Time Series Analysis 1

The basics of time series analysis

##### Time Series Analysis

Learning time series analysis in R