recommendation-system [RecBasics] Negative samples in Top-K recommender task (Part 1) Fundamentals of the Recommendation System [Paper Review] Hybrid Recommender Systems: A Systematic Literature Review (2017) [Paper Review] Wide & Deep Learning for Recommender Systems (2016) deep-learning [CV] Few Shot Learning Pose Estimation - AlphaPose and its application [Paper Review] Neural Translation by Jointly Learning to Align and Translate (2015) [DL 101] Understanding Bi-RNN/LSTM (Pytorch) [Paper Review] Efficient Estimation of Word Representations in Vector Space [Paper Review] U-Net: Convolutional Networks for Biomedical Image Segmentation [DL 101] Activation Functions Useful methods for CV competition [DL 101] RAdam - a novel variant of Adam [DL 101] Learning Rate Scheduler [DL 101] Maxpooling? Convolutions? [DL 101] Upsampling [DL 101] Autoencoder Tutorial (Pytorch) [Jump into ML] Overview of Cross-validation [DL 101] Transfer Learning vs. Fine Tuning vs. Training from scratch [DL 101] List comprehension [DL 101] Early Stopping, Weight Decay [DL 101] Object Recognition Terminology [DL 101] Global Average Pooling [Paper Review] Wide & Deep Learning for Recommender Systems (2016) paper-review [Paper Review] Sequence to Sequence Learning with Neural Networks [Paper Review] Text Understanding with the Attention Sum Reader Network [Paper Review] Distributed Representations of Words and Phrases and their Compositionality [Paper Review] Efficient Estimation of Word Representations in Vector Space [NLP] Google Duplex - 'Jarvis' comes true? [Paper Review] U-Net: Convolutional Networks for Biomedical Image Segmentation [DL 101] Activation Functions [Paper Review] Sparse Transformer [Paper Review] Attention is all you need [NLP] Overview of NLP [Paper Review] Hybrid Recommender Systems: A Systematic Literature Review (2017) [Paper Review] Wide & Deep Learning for Recommender Systems (2016) NLP [Paper Review] Sequence to Sequence Learning with Neural Networks [Paper Review] Text Understanding with the Attention Sum Reader Network [Paper Review] Neural Translation by Jointly Learning to Align and Translate (2015) [DL 101] Understanding Bi-RNN/LSTM (Pytorch) [Paper Review] Distributed Representations of Words and Phrases and their Compositionality [Paper Review] Efficient Estimation of Word Representations in Vector Space [NLP] Google Duplex - 'Jarvis' comes true? [NLP] Big Bird [NLP] Multi-Task Learning & MT-DNN [NLP] NLP tasks [NLP] Code - BERT + KMeans [NLP] How does BERT work? [Paper Review] Attention is all you need [NLP] Difficulties in applying NLP models to Korean data [NLP] Overview of NLP pytorch [DL 101] Understanding Bi-RNN/LSTM (Pytorch) [DL 101] Autoencoder Tutorial (Pytorch) transformer [NLP] Code - BERT + KMeans [NLP] How does BERT work? [Paper Review] Attention is all you need computer vision [CV] Few Shot Learning Pose Estimation - AlphaPose and its application [Paper Review] U-Net: Convolutional Networks for Biomedical Image Segmentation [Paper Review] YOLO (You Look Only Once) [Paper Review] Faster R-CNN [Paper Review] Fast R-CNN [CV] One Shot learning [DL 101] OpenCV python tutorial [Paper Review] R-CNN anomaly-detection [AD] Introducing Anomaly Detection
Team GoGL
M.S. in Statistics & Data Science, Yonsei
Trying to blend in with the A.I. madness