(18) ML-18: 人工智慧概論 - 20, 道瓊指數, LSTM程式

(19) ML-19: MNIST, Multi-Layer Perceptron from Kaggle

(29) ML-29: 用可解釋的人工智慧做影像辨識：(1) CAM

(26) ML-26: Transfer Learning for Analyzing Medical Images

SMIT BActhc 5: Polynomial Regression

(25) ML-25: 3D image classification from CT scans

(20) ML-20: MNIST digits classification dataset and Simple Conv-Net

(30) ML-30: 用可解釋的人工智慧做影像辨識：(2) Grad-CAM

Terence Tao at IMO 2024: AI and Mathematics

AI can't cross this line and we don't know why.

(24) ML-24: Convolutional autoencoder for image denoising

如何使用 CoLab

MIT Introduction to Deep Learning | 6.S191

Generative AI in a Nutshell - how to survive and thrive in the age of AI

(23) ML-23: Classify ImageNet classes with ResNet-50

The Turing Lectures: The future of generative AI

What is generative AI and how does it work? – The Turing Lectures with Mirella Lapata

(15) ML-15: Kaggle

How AI Image Generators Work (Stable Diffusion / Dall-E) - Computerphile

How to run Python programs on: (2) Spyder