สังคมผู้สูงวัยและสังคมเงินสด & blockchain ในญี่ปุ่น

https://www.prachachat.net/asian-100/news-257441

Interpolation VS. Extrapolation

Interpolation means finding unknown data that lies within the range of given values while extrapolation means projecting known data to obtain unknown values.

(https://sciencestruck.com/interpolation-vs-extrapolation)

Chrome Guest mode vs. Incognito

• Incognito just doesn't save browsing history.
• Guest mode neither provides any profile info to any visited web servers nor saves browsing history. (https://support.google.com/chrome/answer/6130773?co=GENIE.Platform%3DDesktop&hl=en)

NECTEC's ML as a Service

https://kitwaicloud.github.io

YOLO v.3

YOLO (You Only Look Once) is primarily designed for object detection, but it also performs object classification as part of the detection process. Here's how both tasks are integrated:

1. Object Detection:

• Detecting Objects: YOLO’s primary task is to detect objects in an image by predicting bounding boxes around them. It determines where objects are located and draws bounding boxes around those objects.

2. Object Classification:

• Classifying Detected Objects: Once YOLO detects the objects and generates bounding boxes, it simultaneously predicts the class (or label) for each object within the bounding box.

Real time object detection program
https://pjreddie.com/darknet/yolo/

Get started https://medium.com/mlearning-ai/getting-started-with-yolov5-in-a-few-minutes-80ea2ff25c3c

Common Vulnerabilities and Exposure (CVE) DBs

https://www.exploit-db.com/

https://cve.mitre.org/

Stat graph:
https://www.exploit-db.com/exploit-database-statistics

เปรียบเทียบ พรบ คอม 50 และ 60

https://thainetizen.org/docs/cybercrime-act-2017/

Free AWS ML

https://aws.amazon.com/th/training/learning-paths/machine-learning/?fbclid=IwAR1kxStHIeSW5wUCBa152GrOu4yGkr_MzILPYPPv3JggWpXOl3WN11B3oHk

ฤดูร้อนช่วยประเทศญี่ปุ่นและอเมริกา

ฤดูร้อนช่วยประเทศญี่ปุ่นให้รอดพ้นจากการโจมตีของมองโกลถึง 2 ครั้งเนื่องจากในช่วงที่มองโกทากองทัพเรือมาถึงญี่ปุ่นในช่วงหน้าร้อนก็เกิดไต้ฝุ่นถึง 2 ครั้งทำให้ต้องถอยทัพ
ในอดีตประเทศอเมริกาเครื่องหนึ่งถูกปกครองโดยฝรั่งเศสแต่ในช่วงหน้าร้อน ยุงที่เป็นพาหะของโรคไข้เหลืองระบาดทำให้กองทัพฝรั่งเศสตายไป 1 ใน 3 ของเซลล์จึงประกาศขายพื้นที่ดังกล่าวทั้งหมดให้กับอเมริกาในราคาถูก

ปัจจัยที่ทำให้ลืม

Web defacement stat

All the information contained in Zone-H's cybercrime archive were either collected online from public sources or directly notified anonymously to us.

http://zone-h.org/archive/special=1

SRAN's stat page:
http://bl.cipat.org/domain_blacklist

Web application automation tool

https://www.seleniumhq.org/

Conversion, Engagement

Conversion is the point at which a recipient of a marketing message performs a desired action.

https://www.dynamicyield.com/glossary/conversion/

Engagement marketing is the use of strategic, resourceful content to engage people, and create meaningful interactions over time.

https://www.marketo.com/engagement-marketing/

A/B testing

คือการแบ่งทดสอบ 2 แนวทาง a และ b ว่าใครเหมาะสมกว่ากัน
hooktalk.com/การทำ-ab-testing-101/

Python VS Matlab

https://pyzo.org/python_vs_matlab.html

Python IDEs
https://www.datacamp.com/community/tutorials/data-science-python-ide?utm_source=adwords_ppc&utm_campaignid=1455363063&utm_adgroupid=65083631748&utm_device=c&utm_keyword=&utm_matchtype=b&utm_network=g&utm_adpostion=1t2&utm_creative=278443377083&utm_targetid=aud-392016246653:dsa-473406587035&utm_loc_interest_ms=&utm_loc_physical_ms=1012728&gclid=CjwKCAiA8rnfBRB3EiwAhrhBGgE-NoEeSozz2GkMw7CEM-RfZnwlb_Szh0EpKbIHRREF9JOkD-NKSRoCImYQAvD_BwE

Python's Math plot library
https://matplotlib.org/users/pyplot_tutorial.html

IoT protocols

https://electronicsforu.com/technology-trends/popular-iot-protocols

Feature selection techniques

Comparison test

• t-test ใช้วัดความแตกต่างของค่าเฉลี่ยของสองกลุ่มว่ามีนัยสำคัญหรือไม่ www.sthda.com/english/wiki/t-test-formula ตย ของ Paired t-test https://www.jmp.com/en_nl/statistics-knowledge-portal/t-test/paired-t-test.html
• ANOVA ใช้วัดความแตกต่างของค่าเฉลี่ยของ 3 กลุ่มขึ้นไปว่ามีนัยสำคัญหรือไม่ http://www.sthda.com/english/wiki/wiki.php?title=one-way-anova-test-in-r#what-is-one-way-anova-test และยังใช้ทำ feature selection ด้วย https://towardsdatascience.com/anova-for-feature-selection-in-machine-learning-d9305e228476
• Friedman test ใช้เมื่อไม่มีสมมติฐานว่า data are normally distributed within each group ไม่เหมือนกับกรณี ANOVA นั่นคือ Fredman test is suitable for non-normal data.
• Nemenyi test is used in conjunction with non-parametric statistical tests, such as the Friedman test, to determine which specific groups (e.g., treatments or methods) are significantly different from each other. (A non-parametric statistical test is a type of statistical test that does not require the data to follow specific assumptions about their underlying distribution, such as normality or homogeneity of variance. These tests are often used when parametric test assumptions are violated, the data are ordinal or ranked, or the sample size is small.)
• Correlation test
• Pearson’s product moment correlation that figure out Pearson’s product moment coefficient (r = [-1,1]) (r^2 is goodness of fit)
• Chi square (X^2) ใช้หา correlation

• Using both traditional feature selection like t-tetst and XAI approaches provides a more robust framework:

  • T-test/Filter methods can quickly filter out features that have zero statistical link to the target, simplifying the initial dataset before model training. The t-test measures the statistical relationship between a single feature and the target variable, independent of any machine learning model.

  • XAI methods are then used after training (unlike other methods that are used before model training) to fine-tune the feature set by identifying features that, while perhaps statistically significant in isolation, are redundant or not utilized by the complex ML model. XAI methods (like SHAP or Permutation Importance) measure a feature's contribution to a specific model's performance and prediction, thereby considering complex feature interactions.

    Studies often show that XAI methods can consistently recover important features that are missed by simple statistics and vice versa, underscoring the value of implementing both.