micahlerner.com
A new year of learning and writing
Published January 12, 2019
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In the spirit of the new year, I am going to attempt to write more often and post most of my writing on my personal blog (with the occasional share to Medium). While I have attempted to write in the past, I am more hopeful that this time will be different, and that the habit will stick.
One of the things that I am excited to write about this year is my personal growth as an engineer. While there are many factors that go into growing as an engineer (mentoring other engineers, communicating clearly with others, etc), a primary component is a desire for continuous learning. I feel lucky to have both the time and energy to hone a skill that I enjoy, and I am looking forward to deepening my technical knowledge in 2019.
On this thread, there are several topics I am eager to dive into greater depth on this year:
- Operating systems and computer networking: I am fascinated by the guts of computers, and engineers like Julia Evans inspire me to learn (and write!) more about the systems that I interact with. Her blog is excellent, and I aspire to document my learning similarly.
- Crypto (where Crypto means cryptography, not ICOs): I’m also excited to learn more about cryptography and crypto engineering. In particular, I would like to sink my teeth into Cryptopals. Other engineers highly recommend it, and solutions are widely available. While it is unlikely that I become a full-blown security engineer, I believe that grokking low-level cryptographic primitives will be generally useful.
- Network Security: Along the trend of deepening my understanding of crypto, operating systems, and networking, I would like to participate in at least one CTF (Capture The Flag) this year, and complete at least one of the wargames out there (like OverTheWire, which I have started, but not completed).
- Machine learning: While I took a Computational Neuroscience class in college, the course mostly focused on theory. The tooling was much different, and two of the major frameworks in use today weren’t even released yet (PyTorch and Tensorflow)! I want to learn more of the mathematical fundamentals behind machine learning and build at least one application of my new knowledge.
While these learning goals seem lofty, I hope that this post is one that I can look at a year from now and feel positively about what I’ve learned. Onward and upward.