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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

Computer Architecture
Operating Systems
Concurrency
Networking
Databases
Distributed Systems
Compilers
Performance Engineering
- Performance Measurement
- Profiling and Observability

Machine Learning

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
- Distributed Training
- Training Parallelism
Inference
Efficiency

Methodology
Working with Papers
Research Practice

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Research

Methodology3 chapters
Working with Papers4 chapters
Research Practice3 chapters

Ethan Hammar·LinkedIn·RSS