Curriculum
2 Sections
20 Lessons
52 Weeks
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Would You Recommend To A Friend?
11
2.1
You, This Course, and Us!
2 Minutes
2.1
What do Amazon and Netflix have in common?
17 Minutes
2.1
Recommendation Engines – A look inside
11 Minutes
2.1
What are you made of? – Content-Based Filtering
14 Minutes
2.1
With a little help from friends – Collaborative Filtering
11 Minutes
2.1
A Neighbourhood Model for Collaborative Filtering
18 Minutes
2.1
Top Picks for You! – Recommendations with Neighbourhood Models
10 Minutes
2.1
Discover the Underlying Truth – Latent Factor Collaborative Filtering
20 Minutes
2.1
Latent Factor Collaborative Filtering contd.
12 Minutes
2.1
Gray Sheep and Shillings – Challenges with Collaborative Filtering
8 Minutes
2.1
The Apriori Algorithm for Association Rules
19 Minutes
Recommendation Systems in Python
9
3.1
Installing Python – Anaconda and Pip
9 Minutes
3.1
Back to Basics : Numpy in Python
18 Minutes
3.1
Back to Basics : Numpy and Scipy in Python
14 Minutes
3.1
Movielens and Pandas
30 Minutes
3.1
What’s my favorite movie? – Data Analysis with Pandas
6 Minutes
3.1
Movie Recommendation with Nearest Neighbour CF
18 Minutes
3.1
op Movie Picks (Nearest Neighbour CF)
6 Minutes
3.1
Movie Recommendations with Matrix Factorization
18 Minutes
3.1
Association Rules with the Apriori Algorithm
10 Minutes
Byte-Sized-Chunks: Recommendation Systems
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You, This Course, and Us!
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