ML4T Academy
A private, offline workbench for studying and researching machine learning for trading. It combines reading, notebooks, a learning mode and an optional AI tutor, all running on your own machine.
Open a chapter or notebook. No connection is needed.
Run and change the code against your own market data.
Ask the local tutor to explain a result, a concept or an error.
Studying machine learning for trading usually means cloud notebooks, scattered material and research questions sent to third-party services.
A desktop workbench pairs the text with runnable notebooks and a guided learning mode. The optional tutor runs on a local language model, so questions and code stay on the machine.
Course text, Jupyter notebooks and your own market data files.
Executed notebooks, notes and a record of exercise progress.
Everything: the content, notebooks, tutor model and history. No account is needed.
Local models are smaller than hosted ones, and the tutor can be wrong. It supports study and does not produce trading signals.