ล้มเร็วเรียนรู้เร็ว

เป็นหลักทางการตลาดว่าให้รีบลงมือทำจะมัวแต่วางแผนจะได้รู้ว่าหมู่หรือจ่า ถ้าล้มเหลวจะได้รีบเอาเวลาไปทำอย่างอื่นแทน

Generative adversarial network (GAN)

A generative adversarial network (GAN) is a class of machine learning systems where two neural networks contest with each other in a game (in the sense of game theory, often but not always in the form of a zero-sum game). Given a training set, GAN learns to generate new data with the same statistics as the training set. For example, a GAN trained on photographs can generate new photographs that look at least superficially authentic to human observers, having many realistic characteristics. Though originally proposed as a form of generative model for unsupervised learning, GANs have also proven useful for semi-supervised learning, fully supervised learning, and reinforcement learning.

https://medium.com/@nutorbitx/gans-%E0%B8%AD%E0%B8%B0%E0%B9%84%E0%B8%A3%E0%B8%84%E0%B8%B7%E0%B8%AD-generative-adversarial-networks-7973ae70db70

The well-known application of GAN is deepfake.

Parsimonious model

A parsimonious model is a model that accomplishes a desired level of explanation or prediction with as few predictor variables as possible.

Pseudonymization vs. Anonymization

Pseudonymization is a data management and de-identification procedure by which personally identifiable information fields within a data record are replaced by one or more artificial identifiers, or pseudonyms.

Anonymization is tokenization.

https://dataprivacymanager.net/pseudonymization-according-to-the-gdpr/

Google data studio

https://datastudio.google.com/u/0/navigation/reporting

Mashup

A mashup (computer industry jargon), in web development, is a web page or web application that uses content from more than one source to create a single new service displayed in a single graphical interface.

--https://en.wikipedia.org/wiki/Mashup_(web_application_hybrid)

Box plot

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

https://www.tableau.com/about/blog/2014/12/5-chart-types-youve-never-tried-tableau-35281

Graph DBMS

https://neo4j.com/

Example graph DBMS is https://neo4j.com/ which claims good performance (equivalent to RDBMS + indexing; the indexing is replaced with graph edges in neo4j).

Java APIs