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cifar10-fast

coursera-ml-andrewng-notes

coursera机器学习笔记

cpp-0-1-resource

C++ 匠心之作 从0到1入门资料

creme

🍨 Online machine learning in Python

ctr-criteo

kaggle 2014 criteo ctr竞赛方案整理 https://www.kaggle.com/c/criteo-display-ad-challenge

ctr_nn

基于深度学习的CTR预估，从FM推演各深度学习CTR预估模型（附代码）

ctr_prediction

CTR prediction using FM FFM and DeepFM

cv-interview

CV岗常见面试题(欢迎大家补充！！！)

d2l-zh

《动手学深度学习》

datascicomp

A collection of popular Data Science Competitions

deep-ctr

An attempt of training DNN models to predict ad click-through rate, implemented with Theano.

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deep-recommender-system

深度学习在推荐系统中的应用及论文小结。

deep-reinforcement-learning

Repo for the Deep Reinforcement Learning Nanodegree program

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deep-reinforcement-learning-papers

A list of recent papers regarding deep reinforcement learning

deep_learning

基础的深度学习实验研究结果汇总笔记

deepctr

This project contains several DNN models for for CTR/CVR implenmented with tf and keras

deepgbm

Implementation for the paper "DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks", which has been accepted by KDD'2019.

deepinterestnetwork

deeplearning

深度学习相关的模型训练、评估和预测相关代码

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为15个章节，近20万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 版权所有，违权必究 Tan 2018.06

deeplearning-mxnet

MXNet for CTR

deeplearningbookqa_cn

深度学习面试问题 回答对应的DeepLearning中文版页码

deeprec

Implementation of Deep Learning based Recommender Algorithms with Tensorflow.

deeprec-1

推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction

deeprl

Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone

details-in-recommendation

Recommender-In-Detail is a package which offers detailed implementations of state-of-the-art techniques and basic methods in recommendation.

dien

dlinterview

Deep Learning Interview 深度学习面试题目汇总