Learn jax4j and Quant
Start with numerical computing in jax4j, or explore the financial models in Quant. Each project has its own curriculum.
jax4j
Tensors, automatic differentiation and accelerated computing in Java 25. Start with the interactive introduction; lessons marked Planned are stubs.
Chapter 0
Getting started
Chapter 1
Working with tensors
Chapter 2
Automatic differentiation
Chapter 3
Capturing and compiling functions
Chapter 4
Batching and randomness
Chapter 5
Control flow and custom derivatives
Chapter 6
Neural networks and optimization
Chapter 7
Execution backends and measurement
quant
Pricing, calibration, risk and CVA. The existing NablaTensor finance curriculum now lives in this section; examples retain their original APIs.
Chapter 0
Orientation: one sweep, every Greek
Chapter 1
Your first pricer
Chapter 2
Every Greek from one sweep
Chapter 3
Payoffs that depend on the whole path
Chapter 4
Picking an engine
Chapter 5
Multi-asset and exotic payoffs
Chapter 6
Early exercise
Chapter 7
Calibration
Chapter 8
Credit
Chapter 9
Risk aggregation
Chapter 10
Regulatory capital
Chapter 11
Counterparty credit risk, deep dive
Chapter 12
Under the hood