hzylf Goto Github PK

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

algorithmsbypython

算法/数据结构/Python/剑指offer/机器学习/leetcode

awesome-algorithm

刷题训练指南

basic-multi-task-learning

This is a repository for Multi-task learning with toy data in Pytorch and Tensorflow

bayesianoptimization

A Python implementation of global optimization with gaussian processes.

bj18

caffe

This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors.

char-rnn-tensorflow

Multi-language Char RNN for TensorFlow >= 1.2.

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

ctr

CTR模型代码和学习笔记总结

ctr-models

TensorFlow implementation of LR, FM, DNN, DeepFM, Deep & Cross Network

deep-ctr-prediction

CTR prediction models based on deep learning(基于深度学习的广告CTR预估模型)

deep-learning-21-examples

《21个项目玩转深度学习———基于TensorFlow的实践详解》配套代码

deep-learning-models

Keras code and weights files for popular deep learning models.

deep_learning

deep learning practice

deep_learning-1

基础的深度学习实验研究结果汇总笔记

deep_learning_estimator

【旧版本】深度学习在推荐算法的ctr预估等场景中的应用，该项目使用tensorflow estimator进行封装，包括dnn、deepfm、din、autoint等模型

deep_learning_estimator_labels

深度学习，针对多目标任务，在推荐算法的ctr预估等场景中的应用，项目使用tensorflow estimator进行封装，包括esmm、mmoe模型

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

docs

TensorFlow documentation

dssm

A BiGRU-Attention DSSM implementation with tensorflow estimator.

fast-neural-style-tensorflow

A tensorflow implementation for fast neural style!

interview

各类经典面试汇总

jd-autobuy

Python爬虫，京东自动登录，在线抢购商品

kddcup_2020_debiasing_1st_place

keras_bert_classification

Bert-classification and bert-dssm implementation with keras.

learning-pyspark

Code repository for Learning PySpark by Packt

machine-learning

Content for Udacity's Machine Learning curriculum

machine-learning-with-pyspark

Source Code for 'Machine Learning with PySpark' by Pramod Singh

machinelearning

Simple Demo of Machine Learning and Deep Learning