TheoremPath
ML Theory & Math Reference
Free · Designed for iPad. Not verified for macOS.
ML theory, prerequisites, notes, review state, and formal theorem context in one iPhone companion for TheoremPath.
TheoremPath is a focused study companion for machine learning theory: prerequisites, theorem statements, notes, review state, and saved progress on iPhone.
Use it when you want a serious map of ML foundations without losing track of
what comes before what. The app pairs the TheoremPath knowledge graph with a
quiet mobile workflow for reading, saving, note taking, and progress review.
What you can do:
- Open Today to continue from your recent work
- Browse the Atlas by topic and prerequisite path
- Save topics for later reading
- Add local notes while studying
- Mark topics as complete
- Track local mastery and due review state
- Complete server-backed daily review and topic practice
- View profile, account, and deletion controls
The content spans probability, statistics, statistical learning theory,
optimization, linear algebra, information theory, concentration inequalities,
and reinforcement learning foundations.
Topics include definitions, theorem statements, assumptions, examples, common
mistakes, and prerequisite chains. The app is designed for learners who care
about structure, proof context, and durable progress.
The library, Atlas, Today, Saved, notes, topic practice, and daily review are free.
Saved-topic bookmarks synchronize when you sign in. Notes and local reading
progress remain on your device.
Terms of Use (EULA): https://www.apple.com/legal/internet-services/itunes/dev/stdeula/
Ratings & Reviews
- This app hasn’t received enough ratings or reviews to display an overview.
Explore the Atlas as a map of topics and their prerequisites, with paths you
can follow through the library. This update refreshes the app's colours and
type, improves dark mode and larger text, and gives articles more room to read.
Loading failures show clearer messages, and bold text around equations stays
within its intended span.
The developer, Robert Sneiderman, indicated that the app’s privacy practices may include handling of data as described below. For more information, see the developer’s privacy policy .
Data Linked to You
The following data may be collected and linked to your identity:
- Purchases
- Contact Info
- User Content
- Identifiers
- Usage Data
- Diagnostics
Data Not Linked to You
The following data may be collected but it is not linked to your identity:
- Identifiers
Accessibility
The developer has not yet indicated which accessibility features this app supports. Learn More
Information
- Seller
- Robert Sneiderman
- Size
- 17.7 MB
- Category
- Education
- Compatibility
Requires iOS 17.0 or later.
- iPhone
Requires iOS 17.0 or later. - iPad
Requires iPadOS 17.0 or later. - Mac
Requires macOS 14.0 or later and a Mac with Apple M1 chip or later. - Apple Vision
Requires visionOS 1.0 or later.
- iPhone
- Languages
- English
- Age Rating
4+
- 4+
- Copyright
- © 2026 Robert Sneiderman