Strojno učenje
s Pythonom do prvega klasifikatorja
Abstract
Knjiga služi kot uvod v področje strojnega učenja za vse, ki imajo vsaj osnovne izkušnje s programiranjem. Pregledajo se pomembni pojmi strojnega učenja (model znanja, učna in testna množica, algoritem učenja), natančneje pa se predstavi tehnika klasifikacije in način ovrednotenja kvalitete modelov znanja klasifikacije. Spozna se algoritem klasifikacije k najbližjih sosedov in predstavi se uporaba tega algoritma – tako konceptualno kakor v programski kodi. Knjiga poda številne primere v programskem jeziku Python in okolju Jupyter Notebooks. Za namen utrjevanja znanja pa so ponujene naloge (tako računske, kot programerske) s podanimi rešitvami.
Keywords
strojno učenje;umetna inteligenca;klasifikatorji;klasifikacija k najbližjih sosedov;Python;učbeniki;
Data
| Language: | Slovenian |
|---|---|
| Year of publishing: | 2022 |
| Typology: | 2.03 - Reviewed University, Higher Education or Higher Vocational Education Textbook |
| Organization: | UM FERI - Faculty of Electrical Engineering and Computer Science |
| Publisher: | Univerza v Mariboru, Univerzitetna založba |
| UDC: | 004.85(075.8)(0.034.2) |
| COBISS: |
94628867
|
| ISBN: | 978-961-286-560-3 |
| Views: | 272 |
| Downloads: | 57 |
| Average score: | 0 (0 votes) |
| Metadata: |
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Other data
| Secondary language: | English |
|---|---|
| Secondary title: | Machine Learning |
| Secondary abstract: | The book serves as an introduction to the field of machine learning for anyone with basic programming experience. Important concepts of machine learning (knowledge model, learning and test set, learning algorithm) are reviewed. More details are given for the classification technique and quality evaluating procedures of classification knowledge models. The classification algorithm k nearest neighbors is presented - both conceptually and in program code. The book provides many examples in the Python programming language and the Jupyter Notebooks environment. For the purpose of consolidating knowledge, several computational and programming exercises with the given solutions are offered. |
| Secondary keywords: | machine learning;artificial intelligence;classification;k nearest neighbors;Python; |
| Type (COBISS): | Higher education textbook |
| Pages: | 1 spletni vir (1 datoteka PDF (158, [2] str.)) |
| DOI: | 10.18690/um.feri.1.2022 |
| ID: | 14373046 |
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