LibRec 精选：BERT原理和应用的图文教程

LibRec 精选

LibRec智能推荐 第 21 期（至2018.12.22），更新 8 篇精彩讨论内容。

初听不知曲中意，再听已是曲中人。 

1

【论文】Enhanced Network Embedding with Text Information (ICPR 2018)，论文：https://github.com/benedekrozemberczki/TENE/blob/master/tene_paper.pdf；代码：https://github.com/benedekrozemberczki/TENE

2

【DeepMind 博客】AlphaZero: Shedding new light on the grand games of chess, shogi and Go，链接：https://aws.amazon.com/blogs/aws/amazon-personalize-real-time-personalization-and-recommendation-for-everyone/

3

【应用】Real-time face detection and emotion/gender classification by a keras CNN and OpenCV（实时人脸检测以及表情/性别分类），源码：https://github.com/oarriaga/face_classification

4

【应用】MLG - Visual Machine Learning Graph of all arXiv papers and researchers（arXiv上机器学习分类下的所有论文和作者的视觉展示），演示：https://arxiv.lyrn.ai/network；示例：https://arxiv.lyrn.ai/citations_network；源码：https://github.com/ranihorev/arxiv-network-graph

5

【教程】The Illustrated BERT, ELMo and co.（BERT原理和应用的图文教程），链接：https://jalammar.github.io/illustrated-bert/

6

【论文】Making Classification Competitive for Deep Metric Learning，链接：https://arxiv.org/abs/1811.12649，摘要：Deep metric learning aims to learn a function mapping image pixels to embedding feature vectors that model the similarity between images. The majority of current approaches are non-parametric, learning the metric space directly through the supervision of similar (pairs) or relatively similar (triplets) sets of images. In this work, we demonstrate that a standard classification network can be transformed into a variant of proxy-based metric learning that is competitive against non-parametric approaches across a wide variety of image retrieval tasks. 

7

【会议】NeurIPS Paper Selection（NeurIPS/NIPS 2018论文解读），链接：https://blog.sicara.com/nips-neurips-papers-selection-28efd4d73189

8

【教程】Training a  Goal-oriented Chatbot with Deep Reinforcement Learning in Python（用深度增强学习实现目标导向的聊天机器人）。

• Introduction and overview of training：

• DQN Agent with Keras：

• Dialogue state tracking：

• User simulator and error model controller：

• Future research

• 链接：https://www.reddit.com/r/MachineLearning/comments/a25owq/p_training_a_goaloriented_chatbot_with_deep/