My Introduction to Computer Science: Machine Learning, LLM & AI
Learning CS & ML from Scratch
When learning a subject from scratch I start with reading some introductory books on the topic. No matter how complicated a subject seems, I always believe I can obtain a working model of it with a few books and an insane reliance on questioning my assumptions.
I’m reminded of Elon Musk’s reliance on first principles and the importance of asking why something matters. The brain is not a very efficient system for retaining facts, especially when those facts are not deemed relevant. Asking why and probing further is the best way to retain knowledge and build on it like a scaffolding system.
My recent interest in Computer Science and Machine Learning sparked with the frenzy around OpenAI. A novice of most things tech, I’ve always shyed away from programming. I’m now obsessed with it. Nothing is greater for learning than an organic interest sparked and fueled by one’s ambition. After seeing what can be done with programming, AI, LLM and machine learning, I’ve embarked on an expansion of my circle of competence.
The real question, what should I read and consume in the realms of computer science and artificial intelligence?
Here is a starting list of learnings:
How Computers Work: The Evolution of Technology, 10th Edition
GPT-4 - How does it work, and how do I build apps with it? - CS50 Tech Talk
Artificial Intelligence - A Modern Approach (Summary)
Harvard CS50’s Introduction to Programming with Python – Full University Course
CS50 offers the introduction to computer science and How Computers Work is really a great starting point. The foundation is set by understanding what computer science is, what computers are, how they interact with each other, etc. These are topics that I have been very ignorant of my whole life. It baffles me to think that I don’t know as much as I could about the technology I use on a daily basis.
Understanding AI and its subcategories are vital for grasping the CS and AI ecosystem. There was a wonderful talk on this, GPT-4 - How does it work, and how do I build apps with it?, I encourage anyone interested in LLMs to watch. A book that is considered a solid resource among CS students is AI: A Modern Approach, which I’ve linked a summary I found on the web. The original is over 1K pages. Another resources I’ve been reading is ML for Absolute Beginners. I recommend it because of its clear and relatively simple language.
Lastly, we need to start programming AI applications, no matter how simple they are. I’ve decided that Python would be the best langauge for me to start with. It’s a simple objected oriented programming language that’s used heavily in the world of finance.
Here’s my current list of learnings… I’m planning to get through the CS50 lectures, and some of the books this month.
As an investor, I’m keeping my eye on companies with AI investments, products and iniciatives. MSFT 0.00%↑ , GOOG 0.00%↑ , and others are being followed. We're interested in seeing the direction of the industry and these giants. Keeping the pulse of the industry through public company filings, private companies, startups and literature is how we'll eventually track the industry and build on our working model.
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