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Collection


A collection of learning notes

Contents

  • 1. Notes on Machine Learning
    • 1.1. Probability Theory
    • 1.2. Machine learning in practice
  • 2. Notes on group theory

1. Notes on Machine Learning

1.1. Probability Theory

Probability theory basics
Bayesian learning
Gaussian process

1.2. Machine learning in practice

Linear algebra in machine learning
Linear prediction
Regularization & cross-validation
L1 Norm and Lasso
Categorical, Dirichlet distribution & Naive Bayes
Optimization
Logistic regression
Neural network

2. Notes on group theory

Lecture note-I
Lecture note-II
Lecture note-III

External Links

Monte Carlo

DISCUS
RMC++
HRMC
fullrmc
RMC for EXAFS
EPSR
RMC at ISIS facility
RMCProfile website
RMCProfile website - legacy
Wikipedia for RMC

Rietveld-like

PDFgui
DIFFPy-CMI
magnetic PDF
Topas for PDF

Tools

ADDIE
Atomeye
Xming
Mantid
GUDRUN
PDFGet..
Neutron scattering length
X-ray form factor
Web elements
Dynamic periodic table
ISIS values

Facilities

US - ORNL - NOMAD
US - ORNL - POWGEN
US - APS - 11-ID-B
US - BNL - 28-ID-1
UK - ISIS - GEM
UK - ISIS - Polaris
UK - Diamond - I15-1
Japan - J-PARC - NOVA
Japan - SPRING8 - BL14B1
Japan - SPRING8 - BL22XU
Europe - ESS - HEIMDAL
China - SSRF - BL13W1
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