definition: software tools and
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Definition: Software tools and techniques working as our personal advisors
Why we are using recommender systems?
Competition
2700+ teams
10% improvement on
Netlfix RMSE (0.9514)
Editorial and hand curated
List of favorites
Simple aggregations
Top-N, Most popular
Tailored to specific users
Netflix, Amazon…
X = Set of Customers
S = Set of Movies
Utility function u: X × S
Rating [1-5]
Gathering “known” ratings for matrix
Predict unknown ratings from the known
Evaluating extrapolation methods
Gathering ratings
Explicit
Implicit
Extrapolating Utilities
Utility matrix U is sparse
Cold start:
New items have no ratings
New users have no history
Term Frequency (TF):
Inverse Data Frequency (IDF):
TF-IDF:
Sentence 1: The car is driven on the road.
Sentence 2: The truck is driven on the highway.
Movies ratings dataset
Anaconda Data Science toolkit
Jupyter Notebook
Data pre-processed using Python Pandas Dataframe
Content-based Recommender System using Python:
sklearn.feature_extraction.text import TfidfVectorizer
Similarities among movies content were computed using Python:
sklearn.metrics.pairwise import linear_kernel
Movies ratings dataset
Anaconda Data Science toolkit
Jupyter Notebook
Data pre-processed using Python Pandas Dataframe
Collaborative-based Recommender System using Surprise Python:
Surprise Singular Vector Decomposition (SVD)
Recommender Systems are not only suggesting, but they help us to make the right decisions
The importance of RS have made researchers to gather every year in The ACM Conference Series of Recommender Systems
Recommender Systems can be scaled to big data (PySpark ALS, and NVIDIA MERLIN)
Francesco Ricci, Lior Rokach, BrachaShapira, and Paul B. Kantor. 2010. Recommender Systems Handbook (1st. ed.). Springer-Verlag, Berlin, Heidelberg.
Charu C. Aggarwal. 2016. Recommender Systems: The Textbook (1st. ed.). Springer Publishing Company, Incorporated.
CS246 | Home (stanford.edu)
Building Recommender Systems with Machine Learning and AI | Udemy
Hands-On Recommendation Systems with Python | Packt (packtpub.com)
NVIDIA MERLIN | NVIDIA Developer
Collaborative Filtering - Spark 2.2.0 Documentation (apache.org)
Mohammed Fayez Rajab | LinkedIn
+971501655392