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AI / ML Animations

LLMs, transformers, RAG, agents, and core machine learning concepts.

ML Foundations

12
Activation Functions
Backpropagation
Bias Variance
Gradient Descent
Linear Regression
Logistic Regression
One-Hot Encoding
Regularization
Cross Validation
Feature Scaling
Optimizers
Vanishing Gradient

Models & Algorithms

12
Decision Tree
K-Means
K-Nearest Neighbors
Naive Bayes
Neural Network
Random Forest
Support Vector Machine
Ensemble
Gradient Boosting
Hierarchical Clustering
PCA
t-SNE

Evaluation

4
Confusion Matrix
Precision-Recall Curve
ROC / AUC
LLM as a Judge

Tokenization & Embeddings

4
BPE
Embeddings Vector Space
Tokenization
Word2vec

Architectures

3
CLIP Alignment
RNN
Vision Transformer (ViT)

Transformers & Attention

11
Multi Head Attention
Self Attention
Transformer Block
Attention Masking
Cross Attention
Flash Attention
Grouped Query Attention
KV Cache
Layer Norm
Positional Encoding
RoPE Positional Encoding

Text Generation

5
Context Window
GPT Generation Loop
Token Sampling
Beam Search
Speculative Decoding

Prompting & Decoding

3
Chain Of Thought
Structured Output
Zero-shot vs One-shot vs Few-shot

RAG & Retrieval

9
Citations Grounding
Graphrag
Hybrid Retrieval
RAG Pipeline
BM25 / TF-IDF
Chunking Strategies
Reranking
Semantic Cache
Vector Search HNSW

Agents

11
Agent Checkpointing
Agent Memory
Agent Workflow Dag
Coding Agent Loop
MCP Protocol
Tool Calling
Agent Planning
Agent Reflection
Multi Agent
React Agent
Tree Of Thought

Training & Fine-tuning

10
Video Diffusion
Diffusion Denoising
DPO
Instruction Tuning
LORA
Mixture Of Experts
QLoRA, 4-bit Fine-Tuning
Quantization
Reward Model
RLHF

ML Systems

6
Gateway
Active Learning
Cascade Models
Distributed Training
Multistage Ranking
Two Tower

MLOps & Monitoring

5
Data Drift
Feature Store
Model Monitoring
Shadow Deployment
Training-Serving Skew