Mining Massive Data Sets 2024

Orodja za analizo velikih podatkovnih baz

Pregledali bomo algoritme strojnega učenja in iskanja znanja v podatkih, ki zmorejo obdelati zelo velike količine podatkov. Predmet se izvaja vzporedno s predmetom Mining massive data sets na Stanford University (prof. Jure Leskovec). 

Predviden čas izvajanja predmeta: januar – marec 2025.

Mining massive data sets

The course will discuss data mining and machine learning algorithms for analyzing very large amounts of data. Topics include:

• MapReduce and Spark
• Frequent itemsets and Association rules
• Near Neighbor Search in High Dimensions
• Locality Sensitive Hashing (LSH)
• Dimensionality reduction: SVD and CUR
• Recommender Systems
• Clustering
• Analysis of massive graphs
• Link Analysis: PageRank, HITS
• Web spam and TrustRank
• Proximity search on graphs
• Large-scale supervised Machine Learning
• Mining data streams
• Learning through experimentation
• Web advertising
• Optimizing submodular functions
  

Assignments and grading:

• 4 homework assignments requiring coding and theory (40%)
• Final exam (30%)
  
• Weekly Colab notebooks (30%)

Useful links:

• Course website: http://web.stanford.edu/class/cs246/
• Handouts (PDF): http://web.stanford.edu/class/cs246/handouts/CS246_Info_Handout.pdf
• Reference book: http://www.mmds.org/

All deadlines at FRI are exactly the same as Stanford deadlines.

Video lectures from past courses:

• 2024: https://snap.stanford.edu/class/cs246-videos-2024/
  username: snap, password: cs246-videos-2024
• 2023: https://snap.stanford.edu/class/cs246-videos-2023/
  username: snap, password: cs246-spring2023-videoarchive
• 2022: https://snap.stanford.edu/class/cs246-videos-2022/
  username: cs246, password: mining2022
• 2019: http://snap.stanford.edu/class/cs246-videos-2019/
• 2018: http://snap.stanford.edu/class/cs246-videos-2018/