Pinned Repositories
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100-Days-Of-ML-Code
100 Days of ML Coding
1806
18.06 course at MIT
AgnosticMeanAndCovarianceCode
Agnostic Mean estimation code for "Agnostic Estimation of Mean and Covariance"
Algorithm_Interview_Notes-Chinese
2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记
algorithms
Bug-tracking for Jeff's algorithms book, notes, etc.
AManPG
Implementation of chenshixiang/AManPG in R, Python, Julia.
POT
Python Optimal Transport library
qreg
Data sparse and non-parametric quantile regression
xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
Gakkilovemath's Repositories
Gakkilovemath/awesome-interpretable-machine-learning
Gakkilovemath/awesome-machine-learning-interpretability
A curated list of awesome machine learning interpretability resources.
Gakkilovemath/base
Scripts for building R on Windows
Gakkilovemath/BigData-Notes
大数据入门指南 :star:
Gakkilovemath/cqr
Conformalized Quantile Regression
Gakkilovemath/d2l-pytorch
This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.
Gakkilovemath/DALEX
Descriptive mAchine Learning EXplanations
Gakkilovemath/data-sketching-and-other-magic-tricks
Materials for a workshop on hash-based sketches
Gakkilovemath/Dive-into-DL-PyTorch
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
Gakkilovemath/donskerclass.github.io
Gakkilovemath/GPyOpt
Gaussian Process Optimization using GPy
Gakkilovemath/interpret
Fit interpretable models. Explain blackbox machine learning.
Gakkilovemath/interpretable_machine_learning_with_python
Practical techniques for training interpretable ML models, explaining ML models, and debugging ML models.
Gakkilovemath/LightGBM-with-Focal-Loss
An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems
Gakkilovemath/lime
Lime: Explaining the predictions of any machine learning classifier
Gakkilovemath/orca
Ordinal Regression and Classification Algorithms
Gakkilovemath/pyFM
Factorization machines in python
Gakkilovemath/pyglrm
The Python wrapper for LowRankModels.jl.
Gakkilovemath/python-introduction
A set of notebooks the provide an introduction to Python.
Gakkilovemath/robust_loss_pytorch
A pytorch port of google-research/google-research/robust_loss/
Gakkilovemath/ROS-Examples
Regression and other stories R examples
Gakkilovemath/sdr_toolbox
Implementation of the most basic SDR (sufficient dimension reduction) methods in Python
Gakkilovemath/shap
A unified approach to explain the output of any machine learning model.
Gakkilovemath/SignalProcessing
About linear dynamic system or LTI system
Gakkilovemath/spark-nlp-workshop
Public runnable examples of using John Snow Labs' NLP for Apache Spark.
Gakkilovemath/talks-and-tutorials
Repository of my conference / meetup talks and tutorials
Gakkilovemath/The-Economist
The Economist 经济学人,持续更新
Gakkilovemath/treeexplainer-study
Code and documentation for experiments in the TreeExplainer paper
Gakkilovemath/useR2019-materials
Links to materials from tutorials and talks from useR 2019
Gakkilovemath/xai_resources
Interesting resources related to XAI (Explainable Artificial Intelligence)