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Title | Inviting Epiphany – A chronicle of insights and |
Description | Inviting Epiphany A chronicle of insights and discoveries Home How Machine Learning Products are Different (Part 2, Entity Resolution Checklists) Last tim |
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WebSite | richardminerich.com |
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US$617,622
Last updated: 2023-05-15 10:11:17
richardminerich.com has Semrush global rank of 17,137,200. richardminerich.com has an estimated worth of US$ 617,622, based on its estimated Ads revenue. richardminerich.com receives approximately 71,265 unique visitors each day. Its web server is located in , with IP address . According to SiteAdvisor, richardminerich.com is safe to visit. |
Purchase/Sale Value | US$617,622 |
Daily Ads Revenue | US$571 |
Monthly Ads Revenue | US$17,104 |
Yearly Ads Revenue | US$205,241 |
Daily Unique Visitors | 4,751 |
Note: All traffic and earnings values are estimates. |
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Inviting Epiphany A chronicle of insights and discoveries Home How Machine Learning Products are Different (Part 2, Entity Resolution Checklists) Last time I talked a bit about the context of my experience with Machine Learning products and the high level issues we had getting customers to switch to what was clearly a better product. This time I get into some technical examples from these checklists and try to demonstrate the conflict. The first and most important distinction between our product and our competitors is we did “ Entity Resolution ” while they did mostly “Name Matching with Rules”. What does this look like in practice? When we built our system our competitors were using name matching systems with rules layered on top. These systems would first create matches based on the textual similarity of the name (based on some fast text matching data structure like a suffix tree). Then, this huge volume of matches would be slimmed down with rules like “only hit if the last name |
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