Implementation of Some of the Big Data Analytics Algorithms in Python
| # | Title | Description |
|---|---|---|
| 1 | Friendship Recommendation | Suggest new friends to individual users based on their mutual friends using PySpark. |
| 2 | Association Rules | Implementation of A-priori algorithm for frequent item set mining and association rule learning. |
| 3 | Locality-sensitive Hashing | Implementation of LSH algorithmic technique that hashes similar input items into the same buckets with high probability. |
| 4 | DGIM Algorithm | DGIM algorithm implementation to find the number 1's in a dataset. |
| 5 | Recommender System | Item-based and user-based collaborative filtering using PySpark. |
| 6 | k-means | k-means clustering algorithm. |
| 7 | Triangle Counting | Implementations of the algorithms for the adjacency list model in the experiments in the paper "Triangle and Four Cycle Counting with Predictions in Graph Streams". |
Rabist - view on LinkedIn
- Course: Advanced Topics (Big Data Analytics) - MS
- Teacher: Dr. Mostafa HaghirChehreghani
- Univ: Amirkabir University of Technology
- Semester: Spring 2022
Licensed under MIT.