Linear algebra concepts are key for understanding and creating machine learning algorithms, especially as applied to deep learning and neural networks. This course reviews linear algebra with applications to probability and statistics and optimization–and above all a full explanation of deep learning.
Curriculum
teacher profile teaching materials
Computations with Large Matrices
Low Rank and Compressed Sensing
Special Matrices
Probability and Statistics
Optimization
Learning from Data
Linear Algebra and Learning from Data,
Wellesley-Cambridge Press
Mutuazione: 20410557 GE530 - ALGEBRA LINEARE PER IL MACHINE LEARNING in Scienze Computazionali LM-40 TERESI LUCIANO
Programme
Highlights of Linear AlgebraComputations with Large Matrices
Low Rank and Compressed Sensing
Special Matrices
Probability and Statistics
Optimization
Learning from Data
Core Documentation
G. Strang,Linear Algebra and Learning from Data,
Wellesley-Cambridge Press
Type of delivery of the course
Theory and practicals with computers; practicals have a noteworthy role in these lecturesType of evaluation
Gli studenti dovranno scegliere un argomento da sviluppare tra quelli presentati durante le lezioni. Dovranno quindi preparare un testo scritto in cui viene descritto il problema, e vengono discussi i risultati degli esperimenti numerici. teacher profile teaching materials
Computations with Large Matrices
Low Rank and Compressed Sensing
Special Matrices
Probability and Statistics
Optimization
Learning from Data
Linear Algebra and Learning from Data,
Wellesley-Cambridge Press
Mutuazione: 20410557 GE530 - ALGEBRA LINEARE PER IL MACHINE LEARNING in Scienze Computazionali LM-40 TERESI LUCIANO
Programme
Highlights of Linear AlgebraComputations with Large Matrices
Low Rank and Compressed Sensing
Special Matrices
Probability and Statistics
Optimization
Learning from Data
Core Documentation
G. Strang,Linear Algebra and Learning from Data,
Wellesley-Cambridge Press
Type of delivery of the course
Theory and practicals with computers; practicals have a noteworthy role in these lecturesType of evaluation
Gli studenti dovranno scegliere un argomento da sviluppare tra quelli presentati durante le lezioni. Dovranno quindi preparare un testo scritto in cui viene descritto il problema, e vengono discussi i risultati degli esperimenti numerici. teacher profile teaching materials
Computations with Large Matrices
Low Rank and Compressed Sensing
Special Matrices
Probability and Statistics
Optimization
Learning from Data
Linear Algebra and Learning from Data,
Wellesley-Cambridge Press
Mutuazione: 20410557 GE530 - ALGEBRA LINEARE PER IL MACHINE LEARNING in Scienze Computazionali LM-40 TERESI LUCIANO
Programme
Highlights of Linear AlgebraComputations with Large Matrices
Low Rank and Compressed Sensing
Special Matrices
Probability and Statistics
Optimization
Learning from Data
Core Documentation
G. Strang,Linear Algebra and Learning from Data,
Wellesley-Cambridge Press
Type of delivery of the course
Theory and practicals with computers; practicals have a noteworthy role in these lecturesType of evaluation
Gli studenti dovranno scegliere un argomento da sviluppare tra quelli presentati durante le lezioni. Dovranno quindi preparare un testo scritto in cui viene descritto il problema, e vengono discussi i risultati degli esperimenti numerici.