At the beginning of the Spring 2023, I was hired as an Undergraduate research assistant, and decided to use the opportunity to learn the basics of Deep Learning.
My goal is to explore and describe deep learning concepts in a language that is easy for me to read and understand. When I encounter difficult mathematical formulas, I will try my best to understand how it was obtained and make sure to detail my process towards understanding.
The cool/scary thing is that... I do not know all the steps in advance, and do not claim that the order I will go about things is the best. In other words, I am carving each new steps as I go, based on what I feel, must focus on.
So, this repository is a journal where I document every learning experiment I conduct. I believe it will be useful for me to look back.
Everything I try (successful or not) will be stored in the form of Jupyter notebooks (and/or python source files). Those artefacts are then grouped in folders with meaningful names.
Each new folder, is a new experiment. Each folder has a number so you have an idea of the order they were created in.
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Andrej Karpathy: I learn from his explanations on YouTube. He provides insights into certain complicated topics. I have admiration for people with deep knowledge on a subject who still take their time to educate in a friendly language. I want to become like that.
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Sebastian Raschka: I read his book Machine Learning book, and find it to be very helpful.
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Lillian Weng: Her blog is very beautiful, well organized, even though most of the content is over my head, haha 😂
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Chris Lattner: Well, I always wanted to build a programming language, and I am curious about his contribution to the field through Modula, his latest venture.