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authorMitja Felicijan <mitja.felicijan@gmail.com>2018-09-21 12:53:51 +0200
committerMitja Felicijan <mitja.felicijan@gmail.com>2018-09-21 12:53:51 +0200
commit90e49e8658c551646dd889a65952ac945d5aba05 (patch)
tree464b2ad0cc6c3a6291512d63d6e56dc5c27715ae
parent11162ab094e2cce2222969af3a851d02c5efb66a (diff)
downloadmitjafelicijan.com-90e49e8658c551646dd889a65952ac945d5aba05.tar.gz
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1<!doctype html>
2<html lang="en">
3
4 <head>
5 <meta charset="utf-8">
6 <title>Title</title>
7 <link rel="icon" type="image/gif" href="/assets/avatar.gif?ver=20180803">
8 </head>
9
10 <body>
11
12 <script src="//cdnjs.cloudflare.com/ajax/libs/remark/0.14.0/remark.min.js"></script>
13 <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS_HTML&delayStartupUntil=configured"></script>
14
15 <script>
16 MathJax.Hub.Config({
17 //displayAlign: 'left',
18 extensions: ['tex2jax.js'],
19 jax: ['input/TeX', 'output/SVG'],
20 tex2jax: {
21 skipTags: ['script', 'noscript', 'style', 'textarea', 'code'],
22 inlineMath: [
23 ['$', '$'],
24 ["\\(", "\\)"]
25 ],
26 displayMath: [
27 ['$$', '$$'],
28 ["\\[", "\\]"]
29 ],
30 }
31 });
32 MathJax.Hub.Configured();
33
34 let slideshow = remark.create({
35 sourceUrl: 'slides.md',
36 ratio: '16:9',
37 mouseWheel: false,
38 });
39
40 </script>
41
42 <style>
43 * {
44 box-shadow: none !important;
45 }
46
47 .remark-container {
48 background-color: #fff !important;
49 }
50
51 table {
52 width: 100%;
53 border-collapse: collapse;
54 border-spacing: 0;
55 }
56
57 table,
58 table td,
59 table th {
60 border: 3px solid #f0f0f0;
61 text-align: left;
62 padding: 10px;
63 }
64
65 img[src$="md-center"] {
66 display: block;
67 margin: 0 auto;
68 }
69
70 img[src$="md-left"] {
71 display: block;
72 margin: 0 auto;
73 }
74
75 img[src$="md-right"] {
76 display: block;
77 margin: 0 auto;
78 }
79
80 img[src$="img350"] {
81 height: 350px;
82 }
83
84 img[src$="img300"] {
85 height: 300px;
86 }
87
88 li {
89 line-height: 200%;
90 }
91
92 h1 {
93 margin-bottom: 150px;
94 }
95
96 h1,
97 h2 {
98 margin-top: 0;
99 }
100
101 h3 {
102 text-align: center;
103 margin-top: 150px;
104 }
105
106 h4 {
107 text-align: center;
108 }
109
110 </style>
111
112 </body>
113
114</html>
diff --git a/slides/math/slides.md b/slides/math/slides.md
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1layout: true
2---
3
4# Why understanding of basic math is imporant for computer programing
5
6September 21, 2018
7
8[@mitjafelicijan](https://twitter.com/mitjafelicijan)
9
10---
11
12### "We Cannot Solve Our Problems With The Same Thinking We Used When We Created Them."
13
14#### — Albert Einstein
15
16---
17
18## How we usually find solutions and why this is problematic?
19
20- We search for code example instead of algorithms.
21- We copy and paste and do testing on trial&error principle.
22- We don't take enough time to properly understand problem we a re trying to solve.
23- Brute force solutions we make are usually not optimized
24
25---
26
27## Math is horrible and I don't need it!
28
29- Well, YES :) Math can be horrible but also beautiful to implement.
30- Disregarding math is disregarding thousands of years of knowledge.
31- Math is not only for scientists.
32- Good algorithm is as optimized as your code is when you are done with it.
33- Math is the search for patterns and anti-patterns in natural universe and making these findings into tools accessible to ordinary people.
34
35---
36
37## Coordinate Geometry
38
39A coordinate geometry is a branch of geometry where the position of the points on the plane is defined with the help of an ordered pair of numbers also known as coordinates.
40
41![image](https://www.onlinemathlearning.com/image-files/xcoordinate-geometry-formula.png.pagespeed.ic.cqp4Ryqey8.png)
42
43---
44
45## Distance formula
46
47![](https://s3.amazonaws.com/ck12bg.ck12.org/curriculum/108383/thumb_540_50.jpg)
48
49---
50
51## Linear Algebra
52
53Linear algebra is the branch of mathematics concerning linear equations such as. linear functions such as. and their representations through matrices and vector spaces.
54
55![image](https://thumbs.gfycat.com/VeneratedSpitefulFrilledlizard-size_restricted.gif)
56
57- [Graphical Linear Algebra](https://graphicallinearalgebra.net/)
58- [Linear Relations](https://graphicallinearalgebra.net/2015/12/26/27-linear-relations/)
59- [Diagrams in charts](https://graphicallinearalgebra.files.wordpress.com/2015/11/ih.gif)
60
61---
62
63## Vectors and spaces
64
65- Space vector also called linear vector
66- Vector = magnitude + direction
67- Example: velocity vector (5kmh/west)
68
69![](https://i.ytimg.com/vi/0oSe9vx-W54/maxresdefault.jpg?img350)
70
71---
72
73## Shortest path problem
74
75In graph theory, the shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized.
76
77Shortest path (A, C, E, D, F) between vertices A and F in the weighted directed graph
78
79![](https://upload.wikimedia.org/wikipedia/commons/thumb/3/3b/Shortest_path_with_direct_weights.svg/250px-Shortest_path_with_direct_weights.svg.png)
80![](http://new.gctm-resources.org/migrating/658-00.png)
81
82[Wiki: Shortest path problem](https://en.wikipedia.org/wiki/Shortest_path_problem)
83
84---
85
86## Dijkstra's shortest path algorithm
87
88![](https://upload.wikimedia.org/wikipedia/commons/5/57/Dijkstra_Animation.gif)
89![](https://upload.wikimedia.org/wikipedia/commons/2/23/Dijkstras_progress_animation.gif)
90
91![](https://cdn-images-1.medium.com/max/735/0*OiVoLu09VJp-oHwJ.png?img300)
92![](https://www.mathworks.com/matlabcentral/mlc-downloads/downloads/submissions/20025/versions/3/screenshot.jpg?img300)
93
94---
95
96## HTML5 Canvas
97
98- [HTML5 Canvas : Matrix Transforms](https://www.w3resource.com/html5-canvas/html5-canvas-matrix-transforms.php)
99- [Visualizing linear algebra using the html5
100canvas: matrices and quaternions](http://archives.math.utk.edu/ICTCM/VOL28/A007/paper.pdf)
101- [Matrix rain animation using HTML5 canvas and javascript](https://codepen.io/riazxrazor/pen/Gjomdp)
102- [Convoluton matrix](https://www.phpied.com/canvas-pixels-2-convolution-matrix/)
103
104---
105
106## Going further
107
108- [Basic Linear Algebra for Deep Learning](https://towardsdatascience.com/linear-algebra-for-deep-learning-f21d7e7d7f23)
109- [Deep learning book](https://www.deeplearningbook.org/contents/linear_algebra.html)
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