mhjensen
38 lines
1.2 KiB
Plaintext
38 lines
1.2 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"<!-- dom:TITLE: Data Analysis and Machine Learning: Elements of Bayesian theory -->\n",
|
|
"# Data Analysis and Machine Learning: Elements of Bayesian theory\n",
|
|
"<!-- dom:AUTHOR: Morten Hjorth-Jensen at Department of Physics, University of Oslo & Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University -->\n",
|
|
"<!-- Author: --> \n",
|
|
"**Morten Hjorth-Jensen**, Department of Physics, University of Oslo and Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University\n",
|
|
"\n",
|
|
"Date: **Dec 13, 2017**\n",
|
|
"\n",
|
|
"Copyright 1999-2017, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"## What is Bayesian Statistics\n",
|
|
"Say something more general here. Reminder about probabilities from the statistics section\n",
|
|
"1. Product rule\n",
|
|
"\n",
|
|
"2. Binomial distribution\n",
|
|
"\n",
|
|
"3. Gaussian PDF\n",
|
|
"\n",
|
|
"4. other PDFs\n",
|
|
"\n",
|
|
"5. Bayesian regression analysis"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|