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用 R 玩 Kaggle –
臉書打卡點預測
Play kaggle with R, Facebook V: Predicting Check Ins
@Mia (R-Ladies)
library(dplyr)
r-ladies_global %>%
filter(from = 'Taipei', travel_to = 'Lisbon')
The Agenda
First Second Third
Hey, Kaggle
# with R-Ladies
# with Masters
Play R
# Warm Up
# EDA, Shiny Apps
# Azure Jupyter
Notebook
Brief Intro
# About
R-Ladies
# About me
2
Last
Q&A
# Recap
# Resource
Sharing
1.
Brief Intro
Intro about R-Ladies and me!
https://rladiestaipei.github.io/R-Ladies-Taipei/
3
R-Ladies Taipei
4
Berl
in
Taiwa
n
4
● Founded in 2014
● every month in Taipei,
● Our history: goo.gl/HbHNeP
Hello!
I am Mia Chang (張懷文).
? Data Scientist, Lecturer
? Member of R-Ladies Taipei
? Co-founder of Azure Taiwan Community
? Microsoft Most Valuable Professionals (MVP) 2017
5
2.
Hey, Kaggle
With R-Ladies and other masters!
6
7
8
9
3.
Play R
# Warm Up - 問題背景,問題定義
# Azure Jupiter Notebook
# use Jupiter access Data
# 結論
10
11
Warm Up -
還沒有modeling經驗的朋友
Warm Up -
關於這個問題背景,問題定義
12
With 8.6 million test records there are about a trillion (10^12)
place-observation combinations.
Warm Up -
關於這個問題背景,問題定義
Schema
row_id
x y
accuracy
time
place_id
13
EDA
“
Warm Up - 關於這個問題背景,問題定義
Three weeks into the eight-week competition,
I climbed to the top of the public leaderboard with
about 50 features
1. the summary data such as the number of historical check ins.
2. historical density of a place candidate, one year prior to the
observation.
3.All features are rescaled if needed in order to result in
similar interpretations for the train and test features.
14
EDA -
Missing data
15
c
EDA -
發現大家透過GPS, Wi-Fi or cellular
16
c
EDA -
尖峰打卡日
17
玩資料 - Shinny App
18
玩資料 - Github
19
玩資料 - Azure Jupyter Notebook
20
玩資料 - Azure Jupyter Notebook
21
# 演算法及結論
#Rcpp
#It was expected that it
would be clearly correlated
with the variation in x and y
but the pattern is not as
obvious. Halfway through the
competition I cracked the
code ...
22
4.
Q&A
# Recap
# Action Item
23
Recap
First Second Third
Hey, Kaggle
# with R-Ladies
# with Masters
Play R
# Warm Up
# EDA, Shiny Apps
# Azure Jupyter
Notebook
Brief Intro
# About
R-Ladies
# About me
24
Last
Q&A
# Recap
# Resource
Sharing
Action Item
First Second Third
Hi, Kaggle Play R
Get your
partners
Visit R-Ladies
R-Basic too!
25
Then
...
Thanks for your listening!
26
Look forward to your visit to R-Ladies Taipei! Also Azure Taiwan!
Bye!
I am Mia Chang (張懷文)
? mia5419@gmail.com
? facebook.com/mia5419
27
28
Take Away & Reference
1.Use EDA to help you find
more feature.
2.Go to Kaggle website to get
more resource to help you:
forum, kernels
3.No matter you are
learning R or you are going
to traveling to visit other
R-Ladies, call us for more
resources :)
1. R-Ladies Meetup Page
2. R-Ladies Facebook Group
3. Blog Post by Tom Van de Wiele
- Detail about implementation
4. Github Repository
5. Shiny App by Tom Van de Wiele
- EDA that you can learn more
6. Kaggle Event Page
7. Microsoft Azure Notebooks

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Play Kaggle with R, Facebook V: Predicting Check Ins