dylanfeehan.github.io/library.html at master · dylanfeehan/dylanfeehan.github.io · GitHub

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
<!DOCTYPE html>
<html>
    <!--<link rel="stylesheets" href="css/main.css">-->
    <body>
        <style>
            .border{
                border-width: 10px;
                border-style: solid;
                border-color: black;
            }
            .larger-image {
                width: 600px;
            }
            body{
                font-family: monospace;
            }
            ul{
                font-size: 20px;
            }
            li{
                font-size: 18px;
            }
            a{
                color: #0000ff
            }
            .bold{
                font-weight: bold;
            }
            .purple{
                color: purple;
            }

        </style>
        <h1>Welcome to the Library!</h1><img class="border larger-image" src="https://bit.ly/fcc-relaxing-cat" alt="Orange cat laying on back" align="right">
        <h2>Programming Books:</h2>
        <ul>Machine Learning
            <li><a href="https://learning.oreilly.com/library/view/hands-on-machine-learning/9781492032632/">Machine Learning: Scikit-learn, Keras, and TensorFlow</a></li>
            <ul>Source Code
                <li><a href="https://github.com/ageron/handson-ml2">Chapter 2 Walkthrough</a></li>
            </ul>
            <li><a href="https://learning.oreilly.com/library/view/introduction-to-machine/9781449369880/">Introduction to Machine Learning with Python</a></li>
            <li><a href="https://learning.oreilly.com/library/view/grokking-artificial-intelligence/9781617296185/">Grokking AI Algorithms</a></li>
            <li><a href="https://learning.oreilly.com/library/view/machine-learning-pocket/9781492047537/">Machine Learning Pocked Reference</a></li>
            <li><a href="https://www.coursera.org/learn/machine-learning/supplement/Mlf3e/more-octave-matlab-resources">Matlab Tutorials</a></li>
        </ul>
        <ul>Deep Learning / Neural Networks
            <li><a href="https://learning.oreilly.com/library/view/deep-learning-for/9781492045519/">Deep Learning for Coders with fastai and PyTorch</a></li>
            <li><a href="https://learning.oreilly.com/library/view/deep-learning-for/9781838640859/">Deep Learning for Beginners</a></li>
            <li><a href="http://neuralnetworksanddeeplearning.com/chap1.html">Neural Networks and Deep Learning</a></li>
            <li><a href="https://learning.oreilly.com/library/view/grokking-deep-learning/9781617293702/">Grokking Deep Learining</a></li>
        </ul>

        <ul>Data
            <li><a href="https://learning.oreilly.com/library/view/data-science-from/9781492041122/">Data Science from Scratch</a></li>
            <li><a href="https://learning.oreilly.com/library/view/python-data-science/9781491912126/">Python Data Science Handbook</a></li>
            <li><a href="https://learning.oreilly.com/library/view/python-for-data/9781491957653/">Python for Data Analysis</a></li>
            <li  class="bold"><a href="https://learning.oreilly.com/library/view/a-common-sense-guide/9781680502794/">A Common-Sense Guide to Data Structures and Algorithms</a></li>
            <ul>
                <li class="purple">Finish chapter 2 and read chapter 3 in the morning, reach chapter 4 at night!!! :)</li>
            </ul>
            <li><a href="https://learning.oreilly.com/library/view/grokking-algorithms/9781617292231/">Grokking Algorithms</a></li>
            <li><a href="https://learning.oreilly.com/library/view/data-science-projects/9781838551025/">Data Science Projects with Python</a></li>
            <li><a href="https://learning.oreilly.com/library/view/hands-on-data-structures/9781788995573/">Data Structures and Algorithms with Python</a></li>
            <li><a href="https://matplotlib.org/gallery.html">matplotlib examples</a></li>
        </ul>

        <ul>Programming Math
            <li><a href="https://learning.oreilly.com/library/view/hands-on-mathematics-for/9781838647292/">Mathematics for Machine Learning</a></li>
            <li><a href="https://www.cs.cornell.edu/~rafael/discmath.pdf">Discrete Math for CS</a></li>
            <li><a href="https://learning.oreilly.com/library/view/the-statistics-and/9781800209763/">Statistics and Calculus with Python Workshop</a></li>
            <li><a href="https://learning.oreilly.com/library/view/statistics-for-machine/9781788295758//">Statistics for Machine Learning</a></li>
            <li><a href="https://learning.oreilly.com/library/view/practical-statistics-for/9781492072935/">Practical Statistics - R and Python</a></li>
            <li><a href="https://learning.oreilly.com/library/view/discrete-mathematical-structures/9789332537415/">Discrete Mathematical Structures</a></li>
        </ul>

        <ul>Python
            <li><a href="https://learning.oreilly.com/library/view/python-crash-course/9781492071266/">Python Crash Course</a></li>
            <li><a href="https://learning.oreilly.com/library/view/automate-the-boring/9781098122584/">Automate the Boring Stuff with Python</a></li>
            <li><a href="https://learnxinyminutes.com/docs/python/">Learn Python</a></li>
            <li><a href="https://learning.oreilly.com/library/view/python-3-object-oriented/9781789615852/">Object-Oriented Programming with python3</a></li>
        </ul>
        <ul>Research Paper Resources
            <li><a href="https://www.microsoft.com/en-us/research/research-area/artificial-intelligence/?facet%5Btax%5D%5Bmsr-research-area%5D%5B0%5D=13556&sort_by=most-recent">Microsoft AI Research Publications</a></li>
            <li><a href="https://www.kdnuggets.com/2017/04/top-20-papers-machine-learning.html">Top 20 Recent Research Papers on Machine learning and Deep Learning</a></li>
        </ul>

        <ul>Datasets
            <ul>Open Repositories
                <li><a href="http://archive.ics.uci.edu/ml/">UC Irvine Machine Learning Repository</a></li>
                <li><a href="https://www.kaggle.com/datasets">Kaggle Datasets</a></li>
                <li><a href="https://registry.opendata.aws/">Amazon's AWS datasets</a></li>
            </ul>
            <ul>Meta Portals
                <li><a href="http://dataportals.org/">Data Portals</a></li>
                <li><a href="http://opendatamonitor.eu/">OpenDataMonitor</a></li>
                <li><a href="http://quandl.com/">Quandl</a></li>
            </ul>
            <ul>Other pages listing many popular open data repositories
                <li><a href="https://homl.info/9">Wikipedia's list of Machine Learning datasets</a></li>
                <li><a href="https://homl.info/10">Quora.com</a></li>
                <li><a href="https://www.reddit.com/r/datasets">The datasets subreddit</a></li>
            </ul>
        </ul>
        <p style="font-size: 18px">Go back <a href="https://dylanfeehan.github.io/" font-size = 16px; >Home</a></p>

    </body>

</html>