selena-wang-1229

selena-wang-1229's Stars

• water8394/BigData-Interview

  :dart: :star2:[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

  1.6k443

• wangzhiwubigdata/God-Of-BigData

  专注大数据学习面试，大数据成神之路开启。Flink/Spark/Hadoop/Hbase/Hive...

  9.7k3.1k

• Frank-LSY/data-interview

  数据分析面试准备

  Language:Jupyter Notebook304

• YunmaoLeo/Data_Analysis_Interview

  数据分析面试

  205

• enhaofrank/Data-mining-or-data-analysis

  数据分析或者数据挖掘工程师面试题整理

  13820

• DiqiangL/bat_code

  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、蔚来笔试、茄子科技笔试、猿辅导笔试等多个互联网大厂，开发，算法笔试真题

  Language:Jupyter Notebook28

• MikeCreken/lanlanInterview

  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

  Language:HTML1.1k108

• sty945/bank_interview

  :bank: 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!）

  5.2k628

• Yimeng-Zhang/feature-engineering-and-feature-selection

  A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

  Language:Jupyter Notebook1.4k408

• alicezheng/feature-engineering-book

  Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018

  Language:Jupyter Notebook1.4k670

• alteryx/featuretools

  An open source python library for automated feature engineering

  Language:Python7.2k878

• huanghanchi/Quant-AI-OR-Math-Statistics

  11624

• youngyangyang04/leetcode-master

  《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！🚀

  Language:Shell51k11.4k

• meagmohit/ml-quant-interview-prep

  Preparation material and resources for the ML (including DL) and Quant Research interviews

  10911

• maiminhp/quanttest

  Jane Street quant interview/test

  889

• muniao/SuperBigData

  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】

  11271

• Rockyzsu/stock

  30天掌握量化交易 (持续更新)

  Language:Python5.1k1.3k

• ranaroussi/quantstats

  Portfolio analytics for quants, written in Python

  Language:Python4.8k844

• yutiansut/QUANTAXIS

  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

  Language:Python8.1k3k

• alexeygrigorev/data-science-interviews

  Data science interview questions and answers

  Language:HTML8.8k2k

• krpiyush5/Amazon-Fine-Food-Review

  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

  Language:Jupyter Notebook3726

• arassadin/image-compression-benchmarking

  Image compression codecs benchmark inspired by Google's "Full Resolution Image Compression with Recurrent Neural Networks"

  Language:Python4017

• 1zb/pytorch-image-comp-rnn

  PyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks

  Language:Python19055

• grammatical/pretraining-bea2019

  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 Systems with Unsupervised Pre-training on Synthetic Data, BEA 2019.

  Language:Shell508

• chenpf1025/noisy_label_understanding_utilizing

  ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels

  Language:Python9023

• NVlabs/noise2noise

  Noise2Noise: Learning Image Restoration without Clean Data - Official TensorFlow implementation of the ICML 2018 paper

  Language:Python1.4k309

• google-research-datasets/C4_200M-synthetic-dataset-for-grammatical-error-correction

  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 dataset are described in more detail by Stahlberg and Kumar (2021) (https://www.aclweb.org/anthology/2021.bea-1.4/)

  Language:Python15424

• kakaobrain/helo-word

  Team Kakao&Brain's Grammatical Error Correction System for the ACL 2019 BEA Shared Task

  Language:Python8922

• grammarly/gector

  Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)

  Language:Python898216

• bentrevett/pytorch-sentiment-analysis

  Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

  Language:Jupyter Notebook4.3k1.2k