Programming For Ai Ai504 Fall Net Worth 2026: Salary, Income & Wealth

Introduction to the class.

Introduction.

Basic machine learning: - Supervised, unsupervised, reinforcement learning - Optimization: Objective function, loss function, ...

Autoencoder: - Implementing & training an autoencoder - Visualizing the reconstructed outputs - Visualizing latent representations ...

Introduction.

BERT & GPT - Word embedding review - Contextualized word embedding (ELMo, GPT-1, BERT) - GPT-2 & GPT-3 & ChatGPT ...

Basic machine learning: - Supervised, unsupervised, reinforcement learning - Optimization: Objective function, loss function, ...

Transformers - Prepare input - Implement Transformer - Train and Evaluate - Visualize attention.

BERT & GPT - Word embedding review - Contextualized word embedding (ELMo, GPT) - BERT - GPT-2 & GPT-3.

Transformer - Self-attention - Multi-head attention - Transformer (encoder) - Positional encoding - Sequence-to-sequence with ...

Autoencoder - Latent representation - Autoencoder - Training process - Visualization - Sparse autoencoder, denoising ...

Introduction.

BERT & GPT - Word embedding review - Contextualized word embedding (ELMo, GPT) - BERT - GPT-2 & GPT-3.