Topic: "fastext"
jeffersonlicet/santander-questions-classification
🥈 Second Place Solution - Public Leaderboard Top 3 - 0.86639 | Clasificación de preguntas de clientes | Escuela de Ciencias Informáticas 2020. Universidad de Buenos Aires y Banco Santander.
Language: Jupyter Notebook - Size: 225 KB - Last synced at: 6 days ago - Pushed at: over 4 years ago - Stars: 6 - Forks: 1
LauriHursti/visions
Recognize Magic: The Gathering (MTG) cards in images by detecting and recognizing their names.
Language: C++ - Size: 18.2 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0
janerjzou/NER
Apply Bi-LSTM with self-attention, attached CRF for Named Entity Recognition.
Language: Jupyter Notebook - Size: 46.9 KB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 1
Hemanth92-stack/DupliFinder-Quora-Clone-Catcher
Detecting duplicate Quora question pairs using ML, deep learning (LSTM, BERT), advanced NLP, feature engineering, and ensemble methods—optimized for accuracy and scalability.
Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: 28 days ago - Pushed at: 28 days ago - Stars: 0 - Forks: 0
mayankmittal29/DupliFinder-Quora-Clone-Catcher
An advanced system for detecting semantically duplicate question pairs using cutting-edge NLP techniques. Combines traditional ML models (XGBoost, SVM, Random Forest) with deep learning architectures (BiLSTM, Siamese Networks, Transformers) and contextual embeddings (BERT, RoBERTa). Features engineered using token similarity, fuzzy matching, and em
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rpnugroho/replicating-product-matching-ndsc
Given the item image and title pairs, to build a model to predict if they are the same or different products.
Language: Jupyter Notebook - Size: 3.25 MB - Last synced at: about 1 year ago - Pushed at: about 4 years ago - Stars: 0 - Forks: 0
