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360 Tech Engineering
360 Tech Engineering
May 21, 2019 · Artificial Intelligence

Understanding Residual Networks: Ideas, Mechanisms, Variants, and Insights

This article reviews the concept of residual networks, explains their working principle and data‑flow interpretation, discusses why they improve deep models, analyzes path‑length effects on gradients, and surveys various residual block designs and practical takeaways.

Model ArchitectureResNetdeep learning
0 likes · 9 min read
Understanding Residual Networks: Ideas, Mechanisms, Variants, and Insights
Xianyu Technology
Xianyu Technology
May 10, 2018 · Artificial Intelligence

Mercari Price Prediction Using TFIDF, GRU, and Ensemble Models

By converting Mercari’s product titles, descriptions, and categorical data into TF‑IDF vectors and embeddings, training MLP and GRU networks, and ensembling them with weighted averaging, the authors achieve a 0.3873 RMSLE—matching the competition’s top score—and demonstrate the power of text‑only price prediction for C2C marketplaces.

GRUTFIDFe-commerce
0 likes · 8 min read
Mercari Price Prediction Using TFIDF, GRU, and Ensemble Models