diff options
| author | TinWoodman92 <chrhodgden@gmail.com> | 2023-12-14 17:32:01 -0600 |
|---|---|---|
| committer | TinWoodman92 <chrhodgden@gmail.com> | 2023-12-14 17:32:01 -0600 |
| commit | c2cd16e922cb8abe206a51e03ae4b711e2c0fba9 (patch) | |
| tree | ca6a8e1787705e0282dd52e73fc8e47258bc7972 /projects_blog | |
| parent | 02843201e8091f9cca4f72ced30eb65dc140b764 (diff) | |
cleaned up <p> element usage.
Diffstat (limited to 'projects_blog')
| -rw-r--r-- | projects_blog/NNetwork.html | 39 |
1 files changed, 17 insertions, 22 deletions
diff --git a/projects_blog/NNetwork.html b/projects_blog/NNetwork.html index 4cabed4..747eb85 100644 --- a/projects_blog/NNetwork.html +++ b/projects_blog/NNetwork.html @@ -3,7 +3,6 @@ <head> <title>chrhodgden - NNetwork</title> <link rel="stylesheet" href="../style.css"/> - <script src="../app.js"></script> </head> <body> @@ -23,16 +22,14 @@ After learning R from a few R tutorials, I decided it was time to learn what machine learning and data science truly was. I had been putting off looking those up because I didn't feel like I was ready. I watched a series on neural networks by 3Blue1Brown on YouTube linked below. - <br> - <br> - <a href="https://youtu.be/aircAruvnKk" target="_blank"> - But what is a neural network? | Chapter 1, Deep learning - </a> - <br> - <br> + </p> + <a href="https://youtu.be/aircAruvnKk" target="_blank"> + But what is a neural network? | Chapter 1, Deep learning + </a> + <p> <i>"Oh, I can do that."</i> I immediately thought to myself. - <br> - <br> + </p> + <p> 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> @@ -40,22 +37,20 @@ <p> I chose R to do this rather than Python because I wanted to build experience with R. This project would be a good demonstration of mixing higher mathmatics with programming, which is what R was built to do. - <br> - <br> + </p> + <p> I did not follow any programming tutorials when developing this. My primary intention was to familiarize myself with the math behind these concepts. I wrote out as much of the program that made sense to me and then referenced YouTube for more detailed topics as I came to them. I primariliy referenced a series by deeplizard on Neural Networks linked below. - <br> - <br> - <a href="https://www.youtube.com/playlist?list=PLZbbT5o_s2xq7LwI2y8_QtvuXZedL6tQU" target="_blank"> - Deep Learning Fundamentals - Intro to Neural Networks - </a> - <br> - <br> + </p> + <a href="https://www.youtube.com/playlist?list=PLZbbT5o_s2xq7LwI2y8_QtvuXZedL6tQU" target="_blank"> + Deep Learning Fundamentals - Intro to Neural Networks + </a> + <p> This series was helpful and taught me about weights and bias initialization, the learning rate, and walked the tedious math sequences in a way that I could follow with my code. - <br> - <br> + </p> + <p> One idea I came up with myself was simple testing process to verify the project worked. I decided to test the network by training it to read binary. This way I would not have to find or build a database of training data, nor label the data. @@ -75,6 +70,6 @@ | <a href="#">Top of Page</a> <hr> </nav> - <script src="app.js"></script> + <script src="../app.js"></script> </body> </html>
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