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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