## Review of 2017

Year 2018 comes soon, at the tail of 2017, I would like to review the whole year,
sum up both professional gains and self-learning gains. This year is a turning
point in my life: I finished my study in school and entered the workplace. Thanks
to the rich education of Toulouse School of Economics and the trust of my
lead, I did my modest part to ...

## Association analysis - Apriori algorithm

Have your heard about the classic use case of association analysis -
“Beer and diaper” at Walmart? In this story, Walmart found
that beer and diapers were often sold together, we can use association analysis
to explain this image.
In this blog, I will introduce some useful concepts and then a use case of
association analysis.
Useful Concepts (...

## france is AI

I participated the conference “france is AI” in this Thursday
and Friday. In this conference, lots of companies and institutes talked about
their thinking of AI, like Google, Microsoft, INS, INSA Rouen, ENSAE. Thanks to
them, I know more about Data Science and AI, and I’d like to share with you some
interesting points.
What is AI?
Rather than ...

## R IN ACTION Review 5 - Time series (Part 3)

In this blog, I’ll introduce ARIMA forecasting models. In the autoregressive
integrated moving average (ARIMA) approach to forecasting, predicted values are
a linear function of recent actual values and recent errors of prediction
(residuals). Before describing ARIMA models, we need to define a number of terms:
lags, autocorrelation, partial aut...

## R IN ACTION Review 4 - Time series (Part 2)

In this blog, we’ll turn to forecasting, starting with popular exponential
modeling approaches that use weighted averages of time-series values[1].
Exponential models are some of the most popular approaches to forecasting the
future values of a time series. They’re simpler than many other types of models,
but they can yield good short-term pred...

## R IN ACTION Review 3 - Time series (Part 1)

I learnt Time Series from “R IN ACTION” in recent days and want to extract some
important points for absorbing and summarizing the knowledge[1]. In this blog, I
will simply introduce the methods for creating and manipulating time series,
describing and plotting them, and decomposing them into level, trend, seasonal,
and irregular (error) compone...

## R IN ACTION Review 2 - Getting started with graphs

This blog reviews general methods for working with graphs. We’ll begin with how
to create and save graphs, then talk about how to modify the features of graph.
Creating and saving graphs
Creating a new graph by issuing a high-level plotting command such as plot(),
hist(), or boxplot() typically overwrites a previous graph. But how to
create mo...

## R: Working with GeoJSON data and resolve 'Error in ogrInfo'

This blog presents how to work with GeoJSON data in R, and proposes the solution of "Error in ogrInfo(dsn = dsn, layer = layer, encoding = encoding, use_iconv = use_iconv"

101 post articles, 13 pages.