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| -rw-r--r-- | img/trained-nn.jpg | bin | 0 -> 3162010 bytes | |||
| -rw-r--r-- | projects_blog/NNetwork.html | 12 | ||||
| -rw-r--r-- | style.css | 7 |
3 files changed, 17 insertions, 2 deletions
diff --git a/img/trained-nn.jpg b/img/trained-nn.jpg Binary files differnew file mode 100644 index 0000000..46f62a4 --- /dev/null +++ b/img/trained-nn.jpg diff --git a/projects_blog/NNetwork.html b/projects_blog/NNetwork.html index 6e10434..e1fd16e 100644 --- a/projects_blog/NNetwork.html +++ b/projects_blog/NNetwork.html @@ -4,7 +4,7 @@ <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>chrhodgden - NNetwork</title> <link rel="icon" type="image/svg+xml" href="../img/favicon.svg"> - <link rel="stylesheet" href="../style.css"/> + <link rel="stylesheet" href="../style.css"> <style> :root { --theme-color-check: 0; @@ -45,6 +45,16 @@ This video series applied old and familiar concepts of linear algebra and multivariable calculus that I had learned in college. Knowing that there were applications of this with data and programming inspired me to try to write some libraries from scratch. </p> + + <figure class="project"> + <img + src="../img/trained-nn.jpg" + alt="Trained Neutal Network" + height="300" + > + <figcaption>My first trained neural network!</figcaption> + </figure> + <h2 id="the-project">The Project</h2> <p> I chose R to do this rather than Python because I wanted to build experience with R. @@ -148,5 +148,10 @@ a:hover { img.self-portrait { float: right; - margin-right: 1rem; + margin: 0.5rem; +} + +figure.project { + float: right; + margin: 0.5rem; }
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