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🎯 🌟[大数据面试题]分享自己在网络上收集的大数据相关的面试题以及自己的答案总结.目前包含Hadoop/Hive/Spark/Flink/Hbase/Kafka/Zookeeper框架的面试题知识总结
专注大数据学习面试，大数据成神之路开启。Flink/Spark/Hadoop/Hbase/Hive...
字节笔试、腾讯笔试、阿里笔试、美团笔试、拼多多笔试、蚂蚁金服笔试、百度笔试、网易笔试、华为笔试、荣耀笔试、oppo笔试、小米笔试、小红书笔试、bilibili笔试、米哈游笔试、携程笔试、快手笔试、大疆笔试、滴滴笔试、得物笔试、科大讯飞笔试、shein笔试、招商银行笔试、深信服笔试、用友笔试、顺丰笔试、微众银行笔试、奇安信笔试、联想笔试、58同城笔试、图森未来笔试、富途笔试、去哪儿笔试、蔚来笔…
此仓库将包含各大银行的基本介绍，笔试面试特点，发现这个宝库就离上岸不远了，哼
🏦 银行笔试面试经验分享及资料分享（help you pass the bank interview, and get a amazing bank offer!）
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
An open source python library for automated feature engineering
《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀
Preparation material and resources for the ML (including DL) and Quant Research interviews
大数据全栈学习【生态组件，技术栈，数据流，数据仓库，数据库，指标体系，血缘关系，元数据管理，数据质量，DataWorks，Hadoop，Spark，Flink，面试，笔记文档，实战练习，公共脚本，常用Shell脚本，Java，Scala，离线，实时，采集，计算，存储，可视化】
Portfolio analytics for quants, written in Python
QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
Data science interview questions and answers
Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review
Image compression codecs benchmark inspired by Google's "Full Resolution Image Compression with Recurrent Neural Networks"
PyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks
Models, system configurations and outputs of our winning GEC systems in the BEA 2019 shared task described in R. Grundkiewicz, M. Junczys-Dowmunt, K. Heafield: Neural Grammatical Error Correction S…
ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
Noise2Noise: Learning Image Restoration without Clean Data - Official TensorFlow implementation of the ICML 2018 paper
This dataset contains synthetic training data for grammatical error correction. The corpus is generated by corrupting clean sentences from C4 using a tagged corruption model. The approach and the d…
Team Kakao&Brain's Grammatical Error Correction System for the ACL 2019 BEA Shared Task
Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.