ishugaepov/Awesome-Machine-Learning-Papers

đŸ“–Notes and remarks on Machine Learning related papers

34
/ 100
Emerging

This collection provides organized academic papers with notes, focusing on techniques to predict how likely customers are to click on ads (CTR) or complete a purchase (CVR). It takes in cutting-edge research papers and provides curated insights. Marketing analysts, data scientists, and advertising strategists working with online ad campaigns would find this useful.

No commits in the last 6 months.

Use this if you need to research advanced methods for improving click-through and conversion rates for online advertising and e-commerce.

Not ideal if you're looking for an off-the-shelf software solution or a tutorial for implementing these models.

online-advertising e-commerce-conversion marketing-analytics ad-tech user-behavior-prediction
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 8 / 25
Community 18 / 25

How are scores calculated?

Stars

47

Forks

16

Language

HTML

License

Last pushed

May 31, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/ishugaepov/Awesome-Machine-Learning-Papers"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.