sucre111's Stars
jindongwang/transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
amanchadha/coursera-deep-learning-specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
jindongwang/transferlearning-tutorial
《迁移学习简明手册》LaTex源码
domokane/FinancePy
A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
jiacai2050/gooreplacer
⚡️⚡️A browser extension to modify HTTP requests :-)
dipanjanS/hands-on-transfer-learning-with-python
Deep learning simplified by transferring prior learning using the Python deep learning ecosystem
wxflogic/logic_vsi
牛津通识读本 Logic: A Very Short Introduction 新译本（补充了第2版新增的两章）
PacktPublishing/Hands-On-Gradient-Boosting-with-XGBoost-and-Scikit-learn
Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt
fgyeason/algorithm-and-risk-management
风控、大数据、算法。
GoogleCloudPlatform/bigquery-data-lineage
Reference implementation for real-time Data Lineage tracking for BigQuery using Audit Logs, ZetaSQL and Dataflow.
finlytics-hub/credit_risk_model
A comprehensive credit risk model and scorecard using data from Lending Club
victorwoo/vimdesktop
让所有 Windows 桌面程序拥有 Vim 操作风格的辅助工具
IBM/xgboost-smote-detect-fraud
Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in this scenario? Find the answers in this code pattern!
salimt/Finance-and-Risk-Management-Algorithms
applications for risk management through computational portfolio construction methods
LogicJake/2020-yizhifu-credit-risk-user-identification-Top2
第二届翼支付杯大数据建模大赛-信用风险用户识别Top2
ali-ghorbani-k/Credit-Risk-Management
A binary classification model is developed to predict the probability of paying back a loan by an applicant. Customer previous loan journey was used to extract useful features using different strategies such as manual and automated feature engineering, and deep learning (CNN, RNN). Various machine learning algorithms such as Boosted algorithms (XGBoost, LightGBM, CatBoost) and Deep Neural Network are used to develop a binary classifier and their performances were compared.
Niranjankumar-c/CreditRiskAnalytics
Predicting the default customers
yiqiyu/tradaboost
The Python implementation of Tradaboost classifier and regressor
andrey-lukyanov/Risk-Management
HSE Course in Risk-Management
jiaqiyao620/credit-risk-management
Class materials of Credit Risk Management taught by prof. Ed Hayes
MichaelCHarrison/XGBoost-with-Python-Notes
Notes on XGBoost
Labryant/RiskManagment
风控学习成长
NeoDG/tradaboost
CPP version, try to make it correctly
sanjin145/RiskManage
风控项目
shenxiangzhuang/sysu-risk-management
Project resources
sucre111/credit-risk-modelling-1
Credit Risk analysis by using Python and ML
sucre111/Home-Credit-Default-Risk
2nd Place Solution 💰🥈
sucre111/hunt-and-peck
Simple vimium/vimperator style navigation for Windows applications based on the UI Automation framework.
sucre111/ML_RiskManagement-1
sucre111/RiskManagment
风控学习成长