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Jeff Park
Mr. Speice
Independent Study and Mentorship
26 September 2019
Machine Learning with TensorFlow
Research Assessment 3
Date: 26 September 2019
Subject: Machine Learning
Works Cited:
Yegulalp, Serdar. "What is TensorFlow? The machine learning library explained."
InfoWorld.com​, 18 June 2019. ​Gale General OneFile​,
https://link.gale.com/apps/doc/A589534891/GPS?u=j043905010&sid=GPS&xid=7cadf7
51. Accessed 26 Sept. 2019.
With the development of open source tools like TensorFlow, accessibility to machine
learning by the average person has never been easier. TensorFlow offers a variety of features that
allow anyone proficient in programming to use it for their own machine learning applications.
This can all be done in the Python programming language, giving me a good opportunity to
experience firsthand what it is like to use machine learning.
The problem with learning how to implement machine learning is the relative scarcity of
resources compared to normal programming. While the article itself does not explain the usage
of TensorFlow, it lists the tools that could be potentially useful for the user. This on its own is
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tremendously helpful for me as I simply do not know enough to know what tools I need to learn
how to use. In addition, the fact that TensorFlow and PyTorch, another machine learning tool,
can be used all within Python, gives me a lot of confidence in my ability to learn more about this
subject. I am already proficient in coding with Python, so the fact that I will be able to learn with
a solid foundation gives me a lot of hope. TensorFlow allows an entry into neural networks
without having to have a comprehensive understanding of the intricate workings of the actual
machine learning algorithms. However, I do plan on gaining a better understanding of machine
learning, so I definitely do not want to use only TensorFlow.
In order to start out, the article recommends using PyCharm for more basic machine
learning applications. PyCharm and TensorFlow both have convenient user interfaces that
display data in graphs. This is good news as having to use third party tools usually lends itself to
having to use the Windows command prompt. This interface is both unintuitive and uninviting,
so having a graphic interface makes using the application very inviting.
The bulk of the TensorFlow libraries are written in C++, making it a very high
performance application. Having experienced firsthand how slow Python can be when dealing
with data that numbers in the thousands of entries, this is very welcoming news. C++ is known to
be extremely light as a programming language, so when using TensorFlow, I should never have
performance issues as I will have to use my laptop hardware, which is very limited in processing
power. However, the versatility of the TensorFlow algorithm means that I should be able to run it
almost anywhere. This will be extremely useful for me when I decide to run these programs on
my phone.
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TensorFlow is a comprehensive machine learning application that has deep learning
capabilities. This makes it an extremely powerful tool for implementing machine learning. At the
same time, it has an easy to use interface and compatibility with Python that entry into machine
learning will be a smooth process for anyone. TensorFlow will surely be a useful tool for my
research in ISM, and these resources only encourage me to learn more about machine learning.
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Annotated Works
Annotated Work