This is where I will be writing my personal notes on
- Mathematics of Machine Learning
- Machine Learning research papers
View notes on Notion here
Hi, I am a undergraduate actively engaged in AI research!
I have a keen interest in the mathematical concepts behind machine learning and staying up-to-date with the ML landscape by regularly reading ML papers.
As someone relatively new to ML, I often encounter complex theories or technicalities that can be overwhelming. I hope my notes can serve as a helpful resource for fellow beginners in the field of ML, just like me.
My interests in ML span areas such as:
- Machine Learning Architecture
- Deep RL
- LLMs
- Computer Vision
- ... and more!
- 17/01/2024 - Probabilistic Graphical Models: Markov Networks [Advanced Concepts]
- 12/01/2024 - Probabilistic Graphical Models: Bayesian Networks [Advanced Concepts]
- 01/01/2024 - Bayesian Learning [Advanced Concepts]
- 27/12/2023 - Confidence Intervals and Hypothesis Testing [Probability and Statistics]
- 27/12/2023 - Sampling and Point Estimation [Probability and Statistics]
- 25/12/2023 - Probability Distributions [Probability and Statistics]
- 24/12/2023 - Introduction to Probability [Probability and Statistics]
- 21/12/2023 - Neural Networks [Calculus]
- 20/12/2023 - Gradient [Calculus]
- 19/12/2023 - Derivatives [Calculus]
- 17/12/2023 - LoRA [ML Paper]
- 17/12/2023 - Determinants and Eigenvectors [Linear Algebra]
- 14/12/2023 - Linear Transformation [Linear Algebra]
- 12/12/2023 - Solving Linear Systems [Linear Algebra]
- 11/12/2023 - Systems of Linear Equations [Linear Algebra]
- 10/12/2023 - Generative Adversarial Networks [ML paper]
- 09/12/2023 - Attention Is All You Need [ML paper]
If you would like to contact me to clarify certain aspects of my notes, I am readily available via:
- Email: t3ohjingxiang@gmail.com