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Machine learning for bestt group - 20170714
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Transcript of Machine learning for bestt group - 20170714
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Machine Learning and CognitiveBy Suwat Hongwiwat, Client Technology Architect, IBM Thailand
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Structured Data
Unstructured Data
Analytics
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Business leaders frequently make decisions based on information they don’t trust, or don’t have1 in3
83%of CIOs cited “Business intelligence and analytics” as part of their visionary plansto enhance competitiveness
Business leaders say they don’t have access to the information they need to do their jobs
1 in2
of CEOs need to do a better job capturing and understanding information rapidly in order to make swift business decisions
60%
… and organizations
need deeper insights
Data is at the center
of a new wave of opportunity…
2.5 million items
per minute
300,000 tweets
per minute
200 million emails
per minute 220,000 photos
per minute
5 TB per flight
> 1 PB per day
gas turbines
1 ZB = 1 billion TB
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Cloud Computing
Easy to Access Computing Power
Available of ready made “as-a-Services”
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Artificial Intelligence
Cognitive Computing
Machine Learning
Deep Learning
Natural Language Processing
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Definition
Machine Learning is a type of Artificial Intelligence that provides the ability to learn
without being explicitly programmed
Artificial Intelligence is the ability of a machine to think and act - Mimics the capability
of human brain in the areas of learning, problem solving etc.
Cognitive computing is the simulation of human thought processes in a computerized
model.
Cognitive computing systems use machine learning algorithms and embedded NLP.
Natural language processing (NLP) is the ability of a computer program to understand
human speech / text as it is spoken.
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What is Machine Learning?
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Machine Learning is computer that can learn to solve problem without specific programming
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Machine Learning have to works with a lot Data
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Continuous learning is key for Machine Learning
Continuous Monitor and Feedback
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Step 1. Start with sample set of actual data with inputs and outputs
Price1. Number of Room2. Area – SQM3. Location
Set of Data Bed room SQM Location Price
1 33 City 3,700,000
2 48 City Edge 4,000,000
3 75 Outside 5,000,000
Input Output
Sample Use case: Condo Seller
“คนเก็งก ำไรซือ้ขำยคอนโด จะตดัสนิใจซือ้ หรอืขำย จำกประสบกำรณข์องเขำ ถำ้เรำจะสอน machine ใหซ้ ือ้ขำยคอนโด เรำจะท ำไดอ้ย่ำงไร?”
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Input 2
Objective of algorithm is to find the value of weight that come out as nearest output value from set of sample data
Step 2. Feed Input data set to machine to calculate using “Algorithm” to get Output
Output
Input 1
Input n
Machine with
Algorithm
Field 1
Field 2
Field 3
Weight1
Weight2
Weight3
Output
Algorithm Calculation
Sample Use case: Condo Seller
OutputOutput
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Step 3. Compare calculated output with actual output and adjust weight in algorithm, then go back to step 2 to get new closer output
Field 1
Field 2
Field 3
Weight1
Weight2
Weight3
Calculated Output
ActualOutputCompare
Sample Use case: Condo Seller
Stop iteration when get minimum different value between calculated and actual
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There are a lot “Algorithm” being used in Machine Learning and Deep Learning is the popular one
Regression Instance-based Regularization Decision Tree
NL Clustering Association Deep Learning
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Machine Learning algorithm can be grouped as 2 models
• Supervised model – Learning by examples , training , target output
Eg: Dad explains his child about different animals and its characteristics (Sound it makes, Apperance etc.)
Implemented for - Tickets problem classification, Face recognition, Image recognition etc.
• Unsupervised model – Learning by experience, no training , no target output
Eg: Visiting a new country withoutknowing about their food, culture,language etc. Learning by experience.
Implemented for – Text analytics,Recommendations etc.
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Machine Learning use cases will deal with large volume of data
Use cases Explaination
Automated loanunderwriting
Machine learning algorithms can be trained on millions of examples of consumer data (age, job, marital status, etc) and financial lending or insurance results (did this person default, pay back the loan on time, get in a car accident, etc). The underlying trends that can be assessed with algorithms, and continuously analyzed to detect trends that might influence lending and insuring into the future
Fraud detection
Machine Learning can learn and monitor users’ behavioral patterns to identify anomalies and warning signs of fraud attempts and occurrences, along with collection of evidence necessary for conviction are also becoming more commonplace in fighting crime.
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People roles involve in Machine Learning
Data Engineering Data Scienctist Business Analysis App Development
Traditional Roles
DBA
ServerAdmin
NW Engineer
DCSpecialist
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What IBM do?
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IBM Machine Learning – Functionality for All!
IBM Watson Machine Learning (on Bluemix)
Data Science Experience with IBM Machine Learning
IBM Machine Learning for z/OS (with DSX)
Data ScientistApp Developer Data Scientist
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IBM Watson Machine Learning as-a-Services
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IBM Data Science Experience
A L L Y O U R T O O L S I N O N E P L A C E
IBM Data Science Experience is an environment that brings together
everything that a Data Scientist needs. It includes the most popular
Open Source tools and IBM unique value-add functionalities with
community and social features, integrated as a first class citizen to
make Data Scientists more successful.
datascience.ibm.com
Powered by IBM Watson Data Platform
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IBM Machine Learning platform – System z
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IBM Machine Learning Platform - PowerAI
Enabled by High Performance Computing Infrastructure
Package of Pre-Compiled Major Deep Learning
Frameworks
Easy to install & get started with Deep Learning with Enterprise-Class Support
Optimized for Performance To Take Advantage of
NVLink
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IBM Machine Learning Infrastructure
S822LC for HPC: recommended configuration for PowerAI2 Socket, 4 GPU System with NVLink
Accelerated
Servers and
Infrastructure for
Scaling
Spectrum Scale:High-Speed Parallel File
System
Scale toCloud
Cluster of NVLink Servers
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Useful Link
What is Machine Learning ?https://www.youtube.com/watch?v=WXHM_i-fgGo
Machine Learning Algorithmshttps://www.youtube.com/watch?v=02R-lZYccEY
Natural language processinghttps://www.youtube.com/watch?v=jubBtD-C9rwhttps://www.youtube.com/watch?v=IKftaqRFyxE
Types of Learninghttps://www.youtube.com/watch?v=gX4ORZ9geyc
Supervised Vs Unsupervised Model Learning https://www.youtube.com/watch?v=nPFnlua2Y5Q
What is Cognitive ?https://www.youtube.com/watch?v=h22n80aT2FY
How IBM Watson Workshttps://www.youtube.com/watch?v=_Xcmh1LQB9I
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Thank You
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