all AI news
Recommender Systems: Lessons From Building and Deployment
Aug. 25, 2022, 4:15 p.m. | Dhruvil Karani
Blog - neptune.ai neptune.ai
If you look at recommender systems papers, a large number of them come from the industry instead of academia. This is because RecSys is actually a practical problem. RecSys for e-commerce could be considerably different than RecSys for social media, as the business objectives differ. In addition, every novel idea needs to be tested in […]
The post Recommender Systems: Lessons From Building and Deployment appeared first on neptune.ai.
building deployment ml model development mlops recommender systems systems
More from neptune.ai / Blog - neptune.ai
Customizing LLM Output: Post-Processing Techniques
3 days, 23 hours ago |
neptune.ai
Deep Learning Optimization Algorithms
1 week, 4 days ago |
neptune.ai
Zero-Shot and Few-Shot Learning with LLMs
1 month, 1 week ago |
neptune.ai
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Research Scientist (Computer Science)
@ Nanyang Technological University | NTU Main Campus, Singapore
Intern - Sales Data Management
@ Deliveroo | Dubai, UAE (Main Office)