I am a huge fan of trying to take the complex, detailed, and unmanageable into a concise, usable and understandable list or outline. I love seeing subjects like data architecture management, data modeling, programming languages, and even Data Science put into visual models that make it easier for others to see conceptually how it exists. […]
If you haven’t gotten a computer science degree you might not have spent much time on the topic of binary trees. Binary Trees are a key concept in the study of algorithms and data structures and are used to implement a binary search tree (BST) and binary heaps, as well as finding applications in efficient searching and sorting algorithms.
Supervised Learning is a topic within Machine Learning that takes a set of “training” data or data that is known to be correct and when applied to other sets of data can attempt to provide correct results.
In order to solve a given problem of supervised learning, one has to perform the […]
In Weiss & Indurkhya’s book “Predictive Data Mining: A practical guide” they write about the “Tasks of Predictive Data Mining”.
“Predictive data mining is goal directed. Representative sample of cases with known answers, summarizing past experiences in meeting these goals. must be in place for predictive mining. Each application has a motivating store that should […]
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases. A learner can take advantage of examples (data)
If you are looking to get a good introduction to data mining and don’t want to dig all over the web to put pieces of information together to get a partial and unreliable view of Data Mining then you need to read Kurt Thearling’s presentation called “Introduction to Data Mining” (pdf |
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