-
Notifications
You must be signed in to change notification settings - Fork 25
/
linear_algebra_resources.html
113 lines (106 loc) · 5.22 KB
/
linear_algebra_resources.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
<!DOCTYPE html>
<html>
<script type="text/javascript">var blog_title = "Linear algebra resources";</script>
<script type="text/javascript">var publication_date = "August 22, 2019";</script>
<head>
<link rel="icon" href="images/ml_logo.png">
<meta charset='utf-8'>
<meta http-equiv="X-UA-Compatible" content="chrome=1">
<link rel="stylesheet" type="text/css" href="stylesheets/stylesheet.css" media="screen">
<link rel="stylesheet" type="text/css" href="stylesheets/print.css" media="print">
<base target="_blank">
<script type="text/javascript" src="javascripts/blog_head.js"></script>
</head>
<body>
<script type="text/javascript" src="javascripts/blog_header.js"></script>
<!-- MAIN CONTENT -->
<div id="main_content_wrap" class="outer">
<section id="main_content" class="inner">
<h3>Linear Algebra for Data Scientists</h3>
<p>
If you're a data scientist studying linear algebra, chances are
you are interested in understanding how machine learning
algorithms work. Neural networks rely on it heavily,
but so do linear regression, factor analysis, and
<a href="https://machinelearningmastery.com/examples-of-linear-algebra-in-machine-learning/">
lots of other methods</a>.
</p>
<p>
The generous professionals of the Internet shared their favorite
linear algebra resources on
<a href="https://www.linkedin.com/posts/brohrer_where-to-learn-calculus-activity-6569183583355887616-Fb8x">
LinkedIn</a> and
<a href="https://twitter.com/_brohrer_/status/1163423524079452163?s=20">
Twitter</a>.
There are a lot of great recommendations here, and I recommend you
scroll through them if you'd like to go deeper into the topic
and catch it from multiple angles.
However, a couple of clear winners emerged.
</p>
<a href="https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab">
<h3>3Blue1Brown, a.k.a. Grant Sanderson</h3>
<img src="images/linear_algebra_3blue1brown.png" width=600
alt="3 Blue 1 Brown You Tube playlist for linear algebra course">
</a>
<p>
Two million YouTube subscribers (to a math channel!) can't be wrong.
Linear algebra concepts lend themselves to illustration,
and the beautiful graphics in these videos exploit this fully.
All the scary terms are explained in straightforward words
and animations. This is a fantastic place to start, partciularly
if you have a touch of anxiety about the topic.
</p>
<p>
My first exposure to linear algebra was not gentle. It consisted
entirely of theorems, proofs, and intimidating words. It was
quite some time after that first course before I started
to build an intuition for the concepts. 3Blue1Brown is the
preparation I wish I'd had then.
</p>
<p>
By the way, if you find the 3Blue1Brown series helpful,
do youself a favor and
<a href="https://www.3blue1brown.com/">support the work</a>.
Grant relies on viewer contributions to support his work.
By donating
you will be giving life blood to unique and inspired
educator, as well as accumulating good karma for yourself.
</p>
<a href="https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/">
<h3>Gilbert Strang</h3>
<img src="images/linear_algebra_gil_strang.png"
alt="Gilbert Strang teaching 18.06 linear algebra" width=600>
</a>
<p>
Professor Strang's lectures for MIT's undergraduate linear
algebra course (18.06) are a crowd favorite. He keeps the
material grounded in computation and application, suiting
it well for the curious data scientist. Professor Strang's mastery
is unquestionable, his ability to break down abstract ideas
into concrete examples is rare, and his passion for
the subject is like nothing I've ever seen.
</p>
<p>
This video series is particularly meaningful to me since it
was recorded in 1999, right when I was taking the course
from him. I wasn't in this particular section. I definitely
was <em>not</em> the guy napping in the eighth row. But
the insights I got during that semester and Professor Strang's
infectious enthusiasm are still fresh.
</p>
<script type="text/javascript" src="javascripts/blog_signature.js"></script>
</section>
</div>
<script type="text/javascript" src="javascripts/blog_footer.js"></script>
<script type="text/javascript">
var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www.");
document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
</script>
<script type="text/javascript">
try {
var pageTracker = _gat._getTracker("UA-10180621-3");
pageTracker._trackPageview();
} catch(err) {}
</script>
</body>
</html>