Kardi Teknomo
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Visit Tutorials below:

Analytic Hierarchy Process (AHP)
Multicriteria decision making
Generalized Mean
Mean and Average
Logarithm Rules
Power rules
Prime Factor
Summation Tricks
Bootstrap Sampling
Convert Decimal to rational
Euler Number
Continued Fraction
PI
Decision tree
Difference equations
Digital Root
Break Even Point
Finding Eigen Value
Ginger Bread Man and Chaos
Micrsoft Excel Tutorial
Excel Iteration
Soving System Equation
Newton Raphson
Root of Polynomial
Sierpinski gasket
Microsoft Excel Macro
ArcGIS tutorial
Graph Theory
Growth Model
k-Means clustering
K Nearest Neighbor
Discriminant analysis
Adaptive Learning from Histogram
Learning from data
Market Basket Analysis
Multi Agent System
LAN Connections Switch
Euler Integration
Ordinary Differential Equation
Runge-Kutta
Bayes Theorem
Conditional Probability
Data Analysis from Questionnaire
Independent Events
Data Revival from Statistics
Recursive Average
Time Average & Time Variance
Generalized Inverse
Regression Model
Kernel Regression
Kernel basis function
Reinforcement Learning
Tower of Hanoi
Similarity and Distance
Normalization of Performance Index
Monte Carlo Simulation
Mean, median, mode
Variance and Standard deviation
System dynamic
Visual Basic (VB) tutorial
Financial Analysis
Sensitivity and What If Analysis

Welcome to Kardi Teknomo's Homepage


Welcome to Kardi Teknomo's Homepage


Hi, Thanks for visiting this page.

Many people said that they enjoy my technical tutorials as well as my self-help ideas, or my research resources. If you found any of them are useful, you may contact me as you please. I would be happy to hear anything from you. Enjoy surfing and please visit again!

What other people say about this web site ...

"Thanks for your article 'how to be Happy'. I think you are right. When people grow become more materialistic … they lost what is called happiness in life. Frankly speaking, I have change my way of thinking about concept of happiness after reading your article. I can create happiness without money. <undisclosed visitor>

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"Great site. Thank you for offering this. With your tutorials, I made more progress in 10 minutes understanding ODEs than the several hours trying to understand the gibberish from several books and other on-line sources." <Dave Newberry>

"..Was the only site i found that actually taught me how to work out the hamming distance..." <anonymous visitor>

"I found your webpage on the k-means clustering algorithm very easy to understand and at the same time they were very informative and easy to understand. Great work" <Paras Jethwani>

" ...thank you for you VB example in k-mean clustering. ...I am psychologist (Russia) and have addjusted your example code in my scientific project (VB)." <Yan’shin Peter Vsevolodovich>

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"an excellent source of information and some very original work in pedestrian simulations" <Crowd Dynamics>

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"your tutorial about KNN algorithm is brief and simple, good job man! it's the clearest kNN explanation i've found!" <Diego Brusetti, Milan, Italy>

"thank you . it's useful for my senior project we are doing our senior project about market basket analysis so we decide to use k-mean clustering" <Suthasinee>

 
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