The Learning Curve

Lecture Notes

• [DM Lecture 02] Part 3 Similarity, Distance and Data Preparation Part1: Understanding Data: Types and CharacteristicsPart2: Data Quality and Statistical DescriptionPart 3: Similarity, Distance and Data Preparation Similarity and distance measures are fundamental concepts in data mining and machine learning. They help quantify how closely related two data objects are. These measures are widely used in clustering, classification, recommendation systems and inf.. 댓글 0 2026.11.02

• [DM Lecture 02] Part 2 Data Quality and Statistical Description Part1: Understanding Data: Types and CharacteristicsPart 2: Data Quality and Statistical DescriptionPart 3: Similarity, Distance and Data Preparation Before applying data mining techniques, it is important to examine the quality and distribution of a dataset. Real-world datasets often contain missing values, duplicate records, inconsistencies and outliers. These issues can affect statistical ana.. 댓글 0 2026.10.30

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  [DM Lecture 02] Part 1 Understanding Data: Types and Characteristics Before applying data mining or machine learning techniques, it is essential to understand the structure and characteristics of the data. Different types of data require different methods of analysis, preprocessing and representation. Choosing an appropriate approach begins with identifying what the data represents, how it is measured, and how it is organised. Part1: Understanding Data: Types and.. 댓글 0 2026.10.25

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  [ML Lecture 01] Introduction to ML 1. Programming in the ModulePythonNumpyPandasScipyMatplotlibKerasPyTorchScikitlearn 2. Machine LearningArtificial Interlligence (AI)Machine Learning (ML) : A subset of AI that enables systems to learn patterns from data, different from traditional solutions relying on explicitly programmed rules. Deep Learning (DL) : A subset of ML based on multi-layerd artificial newral networks, inspired in pa.. 댓글 0 2026.10.13

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  [Lecture 01] Introduction to Data Mining 1. OverviewWhy Do We Need Data Mining? We live in a world where enormous amounts of data are generated every day. However, collecting data does not automatically lead to useful knowledge. The purpose of data mining is to discover meaningful patterns, relationships and insights from data. The growth of data is often described using the 3Vs of Big Data:Volume: The amount of data being generated a.. 댓글 0 2026.10.12