- Collaborative filtering algorithms for recommendations (User - User / Item - Item Recommendations)
- cosine similarity, Finding Image based Similarity
- NLP on client feedback to create score of feedback (Possibly positive / Negative / Neutral based on words used)
- Travelling Salesman problem to identify optimal delivery cycle
- Keep track of every touch point of transaction to predict / pro-active on next move
- Markov chain model - Demand Modelling, This could be classic machine learning model that includes several feature variables (Seasonality / Trend / Style etc..)
- Engineers Shouldn't Write ETL
- Data Platform team enables data scientists to carry algorithm development all the way from concept to production
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