Post on 21-Jan-2018
3
Stevche Radevski
Msc Software Engineering
Working on internal business
support/analytics tools.
Mainly working with JavaScript
(React, React Native, NodeJS)
Cedric Konan
Msc Ubiquitous Computing
Working on Dining services
tools.
Mainly working with Java but
a php lover
Tan Li Boon
Bsc Computer Science
Working on big data with
dev-ops.
Mainly working with Java
(Spark, Couchbase, Hadoop)
6
Play around with Machine Learning
Do something differently
Utilize everyone’s specialized skills and learn from each other
Multiplatform mobile app development
15
A JavaScript based framework to build native, multi-platform mobile applications
1487 official contributors on GitHub
1000+ mobile apps created with it
16
Easy to use (especially if you know React)
Based on JavaScript
Uses markup language syntax
Reusable Components
Very well supported (documentation, active community)
23
No billing surprises
Demonstration of expertise
Specialized Models
A technology company should maintain in-house infrastructure
24
References:
Yoshiyuki Kawano and Keiji Yanai,
The University of Electro-
Communications, Tokyo, Japan
256 food categories, 100
images per category
UEC FOOD-256
25
Inception-v3 is a convolution-based neural network (ConvNet).
It takes 2 to 3 weeks on multiple GPUs to train a ConvNet from zero!
If you need to tweak the network parameters, you have to re-train the whole thing.
Clearly this is not reasonable.
Enter Transfer Learning…
27
Use the outputs of another trained network as generic image feature detectors,
and train a new shallow model using these outputs.
softmax
conv2
conv1
Images and tags
loss
softmax
conv2
conv1
Images and tags
loss
Original Target
Pre-trained
32
Google Vision API
Mine Restaurants Data
Backend API
Vision API
WannaEat Vision
Restaurants.json
Get Tags Per Image
Per Restaurant
Image – Tag
Dictionary
1
2
3
4
5
7
8
6
Store reduced
tags per restaurant
Get 1000 restaurants from Google Maps
Generate tags list
per image
33
Mobile
Google Vision API
Backend API
Vision API
WannaEat Vision
Restaurants.json
User uploaded Image
Image or Tag
Top tag
for image
Matching
Restaurants
36
Collocation is great (no communication friction)
Freedom: Possibility to choose topic and tech stack.
Small team, so no need for long meetings, tickets, wikis (Trello and p2p talk).
Clear system boundaries with clear interfaces between each boundary.
Well-defined responsibilities (but still helping each other)
39
Took some time to remember what we did the last week
Collecting data for restaurants was time-consuming
Vision processing took equally long.
Spent half the time to figure out what problem to tackle
41
Of course we did!
Work in small teams!
Have clearly defined responsibilities
Do one thing at a time (switching between projects takes mental effort)
Machine Learning is not difficult anymore (many API as a service providers)
Rethink best practices (both development and UI/UX)