Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision | ||
|
didattica:magistrale:ml:ay_1819:main [2019/07/15 12:56] marcop [Introduction to Machine Learning (for Ph.D.)] |
didattica:magistrale:ml:ay_1819:main [2020/09/17 16:55] (current) |
||
|---|---|---|---|
| Line 36: | Line 36: | ||
| <WRAP box round 95% center> | <WRAP box round 95% center> | ||
| - | The course intends blablabla.... | + | KNOWLEDGE AND UNDERSTANDING |
| + | |||
| + | The aim of the course is to provide the student with knowledge and skills in the area of machine learning.\\ | ||
| + | At the end of the course the student should be able to: | ||
| + | |||
| + | * distinguish the various machine learning paradigms; | ||
| + | * know the learning theory | ||
| + | * know classification algorithms, regression, clustering and dimension reduction; | ||
| + | |||
| + | |||
| + | APPLYING KNOWLEDGE AND UNDERSTANDING\\ | ||
| + | After completing the course, the student must demonstrate that he is able to: | ||
| + | |||
| + | * apply the different machine learning paradigms | ||
| + | * implement the classification, regression, clustering and dimensionality reduction algorithms; | ||
| + | * design and implement systems able to learn automatically from real data and situations; | ||
| + | |||
| + | |||
| + | COMMUNICATION SKILLS\\ | ||
| + | At the end of this training activity, the student will be able to express himself clearly and with appropriate terms, using the English language, in the learning discussions as well as expose the results of a research concerning technical aspects of machine learning. | ||
| + | |||
| + | LEARNING SKILLS | ||
| + | At the end of this training activity the student will be able to: | ||
| + | |||
| + | * Finding and learning the innumerable algorithms and techniques that are presented in the field of machine learning | ||
| + | * Implementing and using the new algorithms | ||
| + | |||
| </WRAP> | </WRAP> | ||
| Line 44: | Line 70: | ||
| <WRAP round 95% center box> | <WRAP round 95% center box> | ||
| - | * Learning theory and the "learning problem" | + | * Probabilistic learning theory and the "learning problem" |
| - | * The VC-dimension | + | * The VC-dimension (Proof of the maximum margin) |
| * Notions of Probability and Linear Algebra | * Notions of Probability and Linear Algebra | ||
| Line 137: | Line 163: | ||
| * Clustering | * Clustering | ||
| * Neural Networks | * Neural Networks | ||
| - | * pppp | + | * Support Vector Machines |
| - | * pppp | + | * Practical issues for ML |
| ** Material ** | ** Material ** | ||
| Line 147: | Line 173: | ||
| * Lesson4 27/06/2019 {{didattica:magistrale:ml:ay_1819:lezione4_phd_protetto.pdf|Lezione4}} | * Lesson4 27/06/2019 {{didattica:magistrale:ml:ay_1819:lezione4_phd_protetto.pdf|Lezione4}} | ||
| * Lesson5 04/07/2019 {{didattica:magistrale:ml:ay_1819:lezione5_phd_protetto.pdf|Lezione5}} | * Lesson5 04/07/2019 {{didattica:magistrale:ml:ay_1819:lezione5_phd_protetto.pdf|Lezione5}} | ||
| - | * Lesson6 13/07/2019 {{didattica:magistrale:ml:ay_1819:lezione6_phd_protetto.pdf|Lezione6}} | + | * Lesson6 13/07/2019 {{didattica:magistrale:ml:ay_1819:lezione6_protetto.pdf|Lezione6}} |
| </WRAP> | </WRAP> | ||
