seeker1943's starred repositories
reverse-interview-zh
技术面试最后反问面试官的话
deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications
concurrentqueue
A fast multi-producer, multi-consumer lock-free concurrent queue for C++11
Deep-Learning-Interview-Book
深度学习面试宝典(含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向)
KnowledgeGraphCourse
东南大学《知识图谱》研究生课程
awesome-machine-learning-interpretability
A curated list of awesome responsible machine learning resources.
roberta_zh
RoBERTa中文预训练模型: RoBERTa for Chinese
Awesome-algorithm-interview
算法工程师(人工智能CV方向)面试问题及相关资料
FiberTaskingLib
A library for enabling task-based multi-threading. It allows execution of task graphs with arbitrary dependencies.
deep-ctr-prediction
CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)
curated-list-of-awesome-3D-Morphable-Model-software-and-data
The idea of this list is to collect shared data and algorithms around 3D Morphable Models. You are invited to contribute to this list by adding a pull request. The original list arised from the Dagstuhl seminar on 3D Morphable Models https://www.dagstuhl.de/19102 in March 2019.
AIinterview
算法工程师面试题整理
deep-recommender-system
深度学习在推荐系统中的应用及论文小结。
dl-on-flink
Deep Learning on Flink aims to integrate Flink and deep learning frameworks (e.g. TensorFlow, PyTorch, etc) to enable distributed deep learning training and inference on a Flink cluster.
awesome-data-comp-solution
数据科学/人工智能比赛解决方案汇总
word-discovery
速度更快、效果更好的中文新词发现
Recommender-System
推荐系统综述
jstarcraft-rns
专注于解决推荐领域与搜索领域的两个核心问题:排序预测(Ranking)和评分预测(Rating). 为相关领域的研发人员提供完整的通用设计与参考实现. 涵盖了70多种排序预测与评分预测算法,是最快最全的Java推荐与搜索引擎.
awesome-open-source-organizations
⚡️ A list of organizations that have open sourced everything they do
model_compression
Implementation of model compression with knowledge distilling method.
KD_methods_with_TF
Knowledge distillation methods implemented with Tensorflow (now there are 11 (+1) methods, and will be added more.)
PyTorch-On-Angel
PyTorch On Angel, arming PyTorch with a powerful Parameter Server, which enable PyTorch to train very big models.