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Foundations
Linear Algebra
Calculus
- Calculus — Differentiation
- Calculus — Multivariable Calculus
Probability
Statistics
- Statistics — Estimation
- Statistics — Inference and Experimental Design
Optimization
Information and Computation

Computer Science

Algorithms and Data Structures
Theory of Computation

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- Profiling and Observability

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Classical Machine Learning
Neural Networks
Transformers and Language Models
Reinforcement Learning

GPU Computing
Runtimes and Frameworks
- Tensor Runtimes
- Automatic-Differentiation Systems
ML Compilers
- ML Compiler Foundations
- Graph Optimization and Kernel Fusion
Training at Scale
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Inference
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Mathematics

Mathematics

Foundations4 chapters
Linear Algebra3 chapters
Calculus2 chapters
Probability3 chapters
Statistics2 chapters
Optimization3 chapters
Information and Computation3 chapters

Ethan Hammar·LinkedIn·RSS