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Machine Learning Research in blibli
Hendri Karisma
hendri.karisma@gdn-commerce.com / hendri.k.id@ieee.org
Hendri Karisma
• Sr. Research and Development Engineer at
blibli.com (PT. Global Digital Niaga)
• Rnd Team for Data Science/intelligence system
• Working for Fraud Detection System. Current
working in dynamic recommendation system
project.
Definition of Informatics
“Automation of Information” –
Prof. Dr. Ing. Iping Supriana
Machine Learning Definition
“A computer program is said to learn from
experience E with respect to some class of tasks
T and performance measure P, if its performance
at tasks in T, as measured by P, improves with
experience E.” – Prof. Tom Mitchel
How it works
Machine Learning #1
• Supervised
• Unsupervised
• Reinforcement Learning
• Semi-Supervised
• Deep Learning
Machine Learning #2
Machine Learning Taxonomy
JVM Tech (tools) for ML
• weka
• Deeplearning4j (working with spark and GPU)
• H2O (working with spark and GPU, support
Tensorflow, MxNet, and cafe)
• jcuDNN (JNI for wrapping nVidia cuDNN)
• Mahout
• MLlib spark
Artificial Intelligence in Industry
• Fraud Detection System
• Dynamic Recommendation System and User
Profiling
• Traveling Salesman Problem and Binpacking
Problem for better warehouse management
• Social Media Analysis
• Chatbot
• Company condition forecasting
• Governance simulation
The Complexity #1
The Complexity #2
• Big data : volume, variety, velocity, and veracity. (You
might consider a fifth V, value.)
• Knowledge representation or the architecture of the
model
• Unimplemented methods/algorithms in any libraries
• Stack of methods
• Data mostly unlabeled data
• Data resources (microservices)
• Features Engineering (especially from unstructured
data)
• Machines (Hardware)
• High Performance Computing
Stack of Methods
• More complex methods and models
• Methods characteristic & behavior
• Methods customization
• Ex. Semi-supervised, Deep learning, features
engineering
• Sample cases : our research in FDS and
dynamic recommendation system
High Performance Computing
https://hadoop4usa.wordpress.com/2012/04/13/scale-out-up/
Machines
• Cluster machine
• GPU machines (OpenCL and nvidia CUDA)
High Performance Computing #2
• In-memory data fabric: provides low-latency access
and processing of large quantities of data by
distributing data across the dynamic random access
memory (DRAM), Flash, or SSD of a distributed
computer system.
Machine Learning Flow
Scala + Play + Akka + Mongo
The problem is microservices
Next Machine Learning Flow
Scala + Play +
Akka + Mongo +
kafka
New Engine Machine Learning
• Kafka
• Tensorflow (utilize GPU)
• Spark
• Java/Scala/python
Dynamic Collaborative Filtering using HMM
Topological Data Analysis
• Coordinate invariance
• Deformation Invariance
• Compressed Representations
Averi Project
AVERI PROJECT
twitter porn account detection
Example
AVERI PROJECT
twitter prostitution account detection
THANK YOU
Any question?

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