minimal diffusion model for self-study
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Updated
Jul 8, 2023 - Python
minimal diffusion model for self-study
Coursework for self-studying UC Berkeley's CS61A in Spring 2018 (WIP).
Python implementation of RL algorithms presented in Richard Sutton and Andrew Barto's book Reinforcement Learning: An Introduction (second edtion)
Some Python mini projects I create when self-study Python.
Python code for chapter 2 in mml-book
I push my practice codes and experimental codes as I go through my learning process
Coding exercises in the book "Think Python: How to Think Like a Computer Scientist" written by Allen Downey.
Python program to detect red and blue colors from the webcam. OpenCV and Numpy is used..
The 3rd project of cs61c fall 2019. It's a self-study project for me
CS self-study journey: Study guide and notes
Unsupervised Feature Learning / Deep Learning Tutorial
Visualize and make calculations from medical examination data using matplotlib, seaborn, and pandas. The dataset values were collected during medical examinations.
Create a Numpy function outputing the mean, variance, standard deviation, max, min, and sum of the rows, columns, and elements in a 3 x 3 matrix.
Backup of Python Programs
Sandbox for technologies studied during summer '20.
A music mixer built using python pygame to have fun playing around with beats.
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