Corrida do ouro moderna
summary
Describes Shopify Capital’s use of machine learning to predict sales volumes across 100k+ stores, using Python and Apache Spark on large merchant datasets. Covers the end-to-end modeling journey: feature exploration and selection, tuning, deployment options ranging from an operationally isolated gradient-boosted trees model to a deep learning attention model delivering streaming predictions, plus modeling, architecture and optimization techniques aimed at solving business financing decisions.
AI-written summary · about
related talks
51mKeynote Interview
53mMachine Learning in E‑commerce
42mUsing Interconnected ML Models to Tackle Retail Challenges
22mReal-world applications of machine learning: Beyond the hype
02h 00mData Science Driven Business Insights with Python and PySp
38mFantastic ML apps and how to build them
25mUnsupervised shallow learning for fraud detection on marketplaces
22mFrontiers of Machine Learning from the Lens of Retail