enriczhang Goto Github PK
Name: Enric
Type: User
Location: Shenzhen
Name: Enric
Type: User
Location: Shenzhen
100 Days of ML Coding
Exploratory Data Analysis using Pandas, Seaborn and Statsmodels
根据地址提取省、市、区/县、街道,并进行标准化
python地址解析/查区号/查邮编
马上消费金融挑战者大赛-违约用户风险预测--第三名方案
AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库
Automated Machine Learning with scikit-learn
分箱工具
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
评分卡建模自动化流程
Tool for whitebox (binning + logreg) model development
:memo: An awesome Data Science repository to learn and apply for real world problems.
:chart_with_upwards_trend: Curated list of resources to help you get started with Data Science
A curated list of awesome machine learning interpretability resources.
A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading.
💳 The objective is to build a banking behavior scorecard model for HDFC's internal customers through a user's liability account and predict the credit risk.
Statistical standard error estimation tools for correlated data
tool for binning continuous value
Binsembler - A Binwise Ensembler. In general, Ensemble techniques combine the perspective of various models by aggregating the predictions output by each of these models thus tend to enhance the overall prediction accuracy. Simple techniques such as taking majority vote or simple averaging of the predicted probabilities or weighted averaging of predicted probabilities based on model’s F1 score or Accuracy or any other measure are the popular choices to ensemble the model predictions. Here we propose a novel approach based on aggregating the predicted probabilities as weighted averages where weights are the performance statistic based on bins the probabilities fall in. Idea is to divide the predicted probabilities of each model on a validation set into equal sized bins (preferably deciles) and calculate the metrics in each bin. Pick any one metric, and note down it for each bin in a mapping table. This will be the weight used in our weighted ensemble approach. When the prediction to be made on new data, first map the predicted probabilities for the new data to an appropriate bin and then pick the respective metric value for that bin from the mapping table and multiply with the predicted probability. Repeat the same for second model. Finally calculate a new predicted probability as the weighted average.
Bin Stuff - a binning library for R/Python
Python implementations of the Boruta all-relevant feature selection method.
A curated list of practical business machine learning (BML) and business data science (BDS) applications for Accounting, Customer, Employee, Legal, Management and Operations (by @firmai)
Analysis of credit card campaigns.
A library of sklearn compatible categorical variable encoders
FRM & CFA study notes
对数据框中的某个变量进行有监督的分箱操作
招商银行信用卡中心 消费金融场景下的用户购买预测 rank1
一个用于提取简体中文字符串中省,市和区并能够进行映射,检验和简单绘图的python模块
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.