TY  - BOOK
AU  - Forsyth, David
TI  - Applied machine learning
SN  - 9783030181161
AV  - Q325.5.F67 2019 
U1  - 006.3/1 23
PY  - 2019///
CY  - Switzerland
PB  - Springer
KW  - Machine learning
KW  - Textbooks
KW  - Mechanical engineering
KW  - fast
KW  - Maschinelles Lernen
KW  - gnd
KW  - Machine-learning
KW  - gtt
KW  - Leermiddelen (vorm)
KW  - lcgft
N1  - Introduction -- Supervised learning: rationale and basics -- Statistical learning -- Learning with Support Vector Machines (SVM) -- Learning with Neural Networks (NN) -- Fuzzy inference systems -- Data clustering and data transformations -- Decision tree learning -- Business intelligence and data mining : techniques and applications -- Appendix A: Genetic Algorithm (GA) for search optimization -- Appendix B: Reinforcement Learning (RL) -- Datasets from real-life applications for machine learning experiments -- Problems
N2  - "This comprehensive textbook explores the theoretical underpinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning shows, step by step, how to conceptualize problems, acurately represent data, select and tune algorithms, interpret and analyze results, and make informed strategic decisions. Presented in a non-rigorous mathematical syle, the book covers a broad array of machine learning ropics with special emphasis on methods that have been profitably employed." -- back cover
ER  -