Josh Starmer

0:31:11

Coding a ChatGPT Like Transformer From Scratch in PyTorch

0:36:15

Transformer Neural Networks, ChatGPT's foundation, Clearly Explained!!!

0:11:21

p-values: What they are and how to interpret them

0:14:00

Bayes' Theorem, Clearly Explained!!!!

0:00:30

Likelihood vs Probability

0:36:55

Human Stories in AI: Tommy Tang

0:15:51

Attention for Neural Networks, Clearly Explained!!!

0:07:13

Machine Learning Fundamentals: The Confusion Matrix

0:14:41

Hypothesis Testing and The Null Hypothesis, Clearly Explained!!!

0:15:47

The Binomial Distribution and Test, Clearly Explained!!!

0:07:35

The Central Limit Theorem, Clearly Explained!!!

0:06:36

Machine Learning Fundamentals: Bias and Variance

0:05:01

Probability is not Likelihood. Find out why!!!

0:37:27

Human Stories in AI: Simon Stochholm

0:05:13

The Normal Distribution, Clearly Explained!!!

0:35:49

Human Stories in AI: Brian Risk@devra.ai

0:16:35

Entropy (for data science) Clearly Explained!!!

0:03:10

Saturday

0:00:42

The Sensitivity, Specificity, Precision, Recall Sing-a-Long!!!

0:23:43

The matrix math behind transformer neural networks, one step at a time!!!

0:35:31

Human Stories in AI: Fabio Urbina

0:28:25

Human Stories in AI: Amy Finnegan

0:31:13

Human Stories in AI: Rick Marks

0:18:08

Decision and Classification Trees, Clearly Explained!!!