Pinned Repositories
ai-roadmap
ApacheCN AI 路线图(知识树)
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
anchor
Code for "High-Precision Model-Agnostic Explanations" paper
anomaly-detection-resources
Anomaly detection related books, papers, videos, and toolboxes
autogbt-alt
An experimental Python package that reimplements AutoGBT using LightGBM and Optuna.
eli5
A library for debugging/inspecting machine learning classifiers and explaining their predictions
hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Kaggle-Competition-Sberbank
Top 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market
Meta-Learning-Papers
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Python
All Algorithms implemented in Python
mdjabc's Repositories
mdjabc/hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
mdjabc/Meta-Learning-Papers
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
mdjabc/ai-roadmap
ApacheCN AI 路线图(知识树)
mdjabc/autogbt-alt
An experimental Python package that reimplements AutoGBT using LightGBM and Optuna.
mdjabc/awesome-interpretable-machine-learning
mdjabc/awesome-public-datasets
A topic-centric list of HQ open datasets. PR ☛☛☛
mdjabc/awesome-transfer-learning
Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)
mdjabc/Bayesian-Optimization
Code and Example for Bayesian Optimization for LightGBM
mdjabc/Breast-Cancer-Detection-using-deep-belief-network-from-scratch
DBN (deep belief network) implementation for breast cancer detection
mdjabc/Broad-Learning-System
BLS Code
mdjabc/CatBoost
Gradient Boosting with CatBoost.
mdjabc/catboost_graphviz
show tree struct of catboost model by graphviz
mdjabc/Classification
Classification model including XGBoost, GBDT, RandomForest, lightGBM, stacking model...
mdjabc/Classification-with-CatBoost-and-SHAP
I use CatBoost to predict which Amazon employees should get access to certain data and use SHAP to visualise and explain why a certain employee was rejected or granted access.
mdjabc/convnet-interpretability-keras
Visualizing VGG16 Convolutional Neural Network using Keras
mdjabc/deep-transfer-learning-crop-prediction
Deep transfer learning techniques for crop yield prediction, published in COMPASS 2018. Best Note Winner.
mdjabc/DeepLearning_tutorials
The deeplearning algorithms implemented by tensorflow
mdjabc/feature-selection
很简单的特征选择代码实现。
mdjabc/federated
A framework for implementing federated learning
mdjabc/GBDT-XGBoost-LightGBM-CatBoost
mdjabc/iBreakDown_article
Materials for paper about iBreakDown
mdjabc/keras-resnet
Keras package for deep residual networks
mdjabc/LightGBM
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
mdjabc/load-forecasting-resnet
short-term load forecasting with deep residual networks
mdjabc/segam18
Deep-learning seismic facies on state-of-the-art CNN architectures
mdjabc/svm-prediction
机器学习数据,预测趋势并画图
mdjabc/transferlearning
Everything about Transfer Learning and Domain Adaptation--迁移学习
mdjabc/tutorials
CatBoost tutorials repository
mdjabc/xgboost-lightgbm-hyperparameter-tuning
Bayesian Optimization and Grid Search for xgboost/lightgbm
mdjabc/XLC
Tools of XGBoost, LightGBM and CatBoost