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Adding motivation to BNN

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mhjensen
2019-06-08 20:03:19 -04:00
parent 26610911ad
commit 00d4e6e22f
12 changed files with 129 additions and 71 deletions
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doc/web/course.do.txt
+2 -2
View File
@@ -18,7 +18,7 @@ chapters = {
'Linalg': 'Review of central linear algebra elements',
'Statistics': 'Monte Carlo methods and elements of probability theory',
'Regression': 'Regression Methods',
'Splines': 'Gradient methods',
'Splines': 'Gradient methods and Minimization Algorithms',
'LogReg': 'Logistic Regression',
'NeuralNet': 'Neural Networks',
'DimRed': 'Reduction of dimensionality',
@@ -29,7 +29,7 @@ chapters = {
'Autoencoders': 'Autoencoders',
'Reinforce': 'Reinforcement Learning',
'odenn': 'Solving ordinary and partial differential equations with Neural Networks',
'Bayesian': 'Elements of Bayesian theory',
'Bayesian': 'Elements of Bayesian theory and Bayesian Neural Networks',
'summary': 'Summary',
}
%>
doc/web/course.html
+11 -4
View File
@@ -6,6 +6,7 @@ Automatically generated HTML file from DocOnce source
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<meta name="description" content="Overview of course material: Data Analysis and Machine Learning">
<title>Overview of course material: Data Analysis and Machine Learning</title>
@@ -83,7 +84,10 @@ div { text-align: justify; text-justify: inter-word; }
None,
'___sec4'),
('Regression Methods', 2, None, '___sec5'),
('Gradient methods', 2, None, '___sec6'),
('Gradient methods and Minimization Algorithms',
2,
None,
'___sec6'),
('Logistic Regression', 2, None, '___sec7'),
('Neural Networks', 2, None, '___sec8'),
('Reduction of dimensionality', 2, None, '___sec9'),
@@ -104,7 +108,10 @@ div { text-align: justify; text-justify: inter-word; }
2,
None,
'___sec16'),
('Elements of Bayesian theory', 2, None, '___sec17'),
('Elements of Bayesian theory and Bayesian Neural Networks',
2,
None,
'___sec17'),
('Summary', 2, None, '___sec18'),
('Python and Scikit Learn, a short guide', 2, None, '___sec19'),
('Teach yourself C++', 2, None, '___sec20'),
@@ -366,7 +373,7 @@ formulas in HTML or ipython notebook files.
</ul>
<h2 id="___sec6">Gradient methods </h2>
<h2 id="___sec6">Gradient methods and Minimization Algorithms </h2>
<ul>
<li> LaTeX PDF:</li>
@@ -685,7 +692,7 @@ formulas in HTML or ipython notebook files.
</ul>
<h2 id="___sec17">Elements of Bayesian theory </h2>
<h2 id="___sec17">Elements of Bayesian theory and Bayesian Neural Networks </h2>
<ul>
<li> LaTeX PDF:</li>