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/POT
Python Optimal Transport library
Gakkilovemath/AManPG
Implementation of chenshixiang/AManPG in R, Python, Julia.
Gakkilovemath/aml_bayes
Code for the paper: Adversarial Machine Learning: Bayesian Perspectives
Gakkilovemath/awesome-self-supervised-learning
A curated list of awesome self-supervised methods
Gakkilovemath/bayesoptbook.github.io
Companion webpage for the book "Bayesian Optimization" by Roman Garnett
Gakkilovemath/brglm2
Estimation and inference from generalized linear models using explicit and implicit methods for bias reduction
Gakkilovemath/chebpy
A Python implementation of Chebfun
Gakkilovemath/coding-for-economists
This repository hosts the code behind the online book, Coding for Economists.
Gakkilovemath/dmol-book
Deep learning for molecules and materials book
Gakkilovemath/falkon
Large-scale, multi-GPU capable, kernel solver
Gakkilovemath/get-started-with-JAX
The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
Gakkilovemath/gpss_labs
Repository for labs
Gakkilovemath/jax_notebooks
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022
Gakkilovemath/lassonet
Feature selection in neural networks
Gakkilovemath/liboptpy
Implementation of various optimization methods
Gakkilovemath/LMP
Linear Models with Python
Gakkilovemath/matrixcalc
MIT IAP short course: Matrix Calculus for Machine Learning and Beyond
Gakkilovemath/ML_course
EPFL Machine Learning Course, Fall 2021
Gakkilovemath/MLatImperial2022
Gakkilovemath/newcorrelationstatistics
xi correlation method adapted for python
Gakkilovemath/numerical-tours
Numerical Tours of Signal Processing
Gakkilovemath/optimization_course
A course on Optimization Methods
Gakkilovemath/optiver-trading-close
Gakkilovemath/probai-2022
Materials of the Nordic Probabilistic AI School 2022.
Gakkilovemath/pyHSICLasso
Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data
Gakkilovemath/pyprobml
Python code for "Probabilistic Machine learning" book by Kevin Murphy
Gakkilovemath/RL-book
Gakkilovemath/scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
Gakkilovemath/scikit-fda
Functional Data Analysis Python package
Gakkilovemath/seminars-fivt
Seminars on optimization methods