Oct 06

lecture 02 object oriented programming in PHP 5

https://youtu.be/QJSYVubQTfg

Sep 29

lecture 02 game design components and process

https://youtu.be/OqoY7Xazf7Q

Sep 22

lec 7 accuracy sensor measures

https://youtu.be/ZzuRy_y-xW0

Sep 15

lec 6 based on time measures

https://youtu.be/7qTcR9w8R7U

Sep 13

AI and Machine Learning Algorithms: Part – 5 (Polynomial Regressions)

Sep 01

lec 2 performance measurement categories for performance measurements of tracking applications such

https://youtu.be/p88UOH_QPXk

Aug 29

Misc. Models in Machine Learning

Factor Analysis:

GPCM/GGPCM:

GPCM Gaussian Process Convolution Model

Generalised Gaussian Process Convolution Model (GGPCM), which is a generalisation of the Gaussian Process Convolution Model presented by Tobar et al.

https://www.mlmi.eng.cam.ac.uk/files/wessel_bruinsma_8224721_assignsubmission_file_bruinsma_wessel_dissertation.pdf

What is GPCM Model? Generic Predictive Computational Model 

Example Research on GPCM: https://ieeexplore.ieee.org/document/9944777

https://en.wikipedia.org/wiki/Mixture_model

https://www.sciencedirect.com/topics/medicine-and-dentistry/mixture-model

Aug 26

Normal/Gaussian Distribution: Understanding data for Machine Learning and Data Science Projects.

Normal/Gaussian Distribution: Bell Curve

https://mathworld.wolfram.com/NormalDistribution.html

Univariate Normal Distribution:

BiVariate Normal/Gaussian Distribution

https://www.probabilitycourse.com/chapter5/5_3_2_bivariate_normal_dist.php

Multi Variate Random variable

https://en.wikipedia.org/wiki/Multivariate_normal_distribution

Aug 25

Misc. Plots for Data Science Projects

https://www.researchgate.net/figure/Doubledecker-plot-for-the-OvaryCancer-data-showing-the-conditional-distribution-of-X-ray_fig13_5142958

Titanic Dataset: Double Decker Plot

https://www.researchgate.net/figure/Titanic-data-Class-Gender-Age-and-Survival-a-joint-independence-b-main-effects_fig3_2508823

Berkeley Admission Data:

https://www.thoughtco.com/uc-berkeley-admissions-787148

Geyser Data: With Contours

https://www.r-bloggers.com/2016/10/assessing-clustering-tendency-a-vital-issue-unsupervised-machine-learning/

Aug 25

What are Association rule and APriori Algorithm. How to calculate the related measures.

Apriori[1] is an algorithm for frequent item set mining and association rule learning over relational databases. It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database. The frequent item sets determined by Apriori can be used to determine association rules which highlight general trends in the database: this has applications in domains such as market basket analysis.

https://www.ibm.com/topics/apriori-algorithm#:~:text=The%20Apriori%20algorithm%20is%20an,items%20called%20itemsets%20in%20data.

—

I know not that clear

https://www.solver.com/xlminer/help/association-rules#:~:text=In%20association%20analysis%2C%20the%20antecedent,consequent%20parts%20of%20the%20rule.

https://www.ibm.com/docs/sl/sdm/18.0.0?topic=settings-association-rule-scoring-options

Calculation:

Ref: https://rasbt.github.io/mlxtend/user_guide/frequent_patterns/association_rules/

https://www.kdnuggets.com/2016/04/association-rules-apriori-algorithm-tutorial.html

Support

Confidence:

Lift