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 # TensorLib
 
-A minimal, dependency-free C++23 tensor computation library designed for low-level ML infrastructure development and numerical computing research.
+TensorLib is a C++23 tensor computation library geared toward low-level ML infrastructure work and numerical computing research. It provides a small, fast core with explicit control over memory, shape handling, and numerical operations, plus optional utilities for CSV ingestion and simple data loading.
+
+## Features
+- Tensor creation helpers (zeros, ones, random initializers, scalars)
+- Shape/rank management with row-major indexing
+- Elementwise arithmetic with broadcasting
+- Matrix multiplication and 2D transpose
+- Common activations and scalers (sigmoid, ReLU, tanh, min/max/standard scalers)
+- Lightweight autograd graph registry (node tracking)
+- CSV parsing utilities and tensor conversion helpers
+
+## Repository Layout
+- `tensor/` — core tensor and ops implementation (`tensorlib` static library)
+- `csvlib/` — CSV parsing utilities (`csvlib` static library)
+- `dataLoader/` — CSV-to-tensor helpers (`dataLoader` static library)
+- `apps/` — example applications
+- `benchmarks/` — performance benchmarks
+- `tests/` — unit tests
+
+## Requirements
+- C++23 toolchain
+- CMake 3.20+
+- Eigen3 (used by tests/benchmarks; fetched automatically if not installed)
+- GoogleTest and Google Benchmark (fetched automatically via CMake)
+
+## Build
+```bash
+cmake -S . -B build
+cmake --build build
+```
+
+## Usage (Minimal Example)
+```cpp
+#include <tensorlib/ops.h>
+#include <tensorlib/tensor.h>
+
+int main() {
+    auto a = Tensor::createOnes({2, 3});
+    auto b = Tensor::createOnes({3, 2});
+    auto c = TensorOps::matmul(a, b);
+    return 0;
+}
+```
+
+## Tests
+```bash
+ctest --test-dir build
+```
+
+## Benchmarks
+```bash
+./build/benchmarks/bench_tensor
+```
+
+## Applications
+- `linearRegression` — simple linear regression over CSV data (see `apps/linearRegression.cpp`)
+- `test` — placeholder app
+
+## License
+See [LICENSE](LICENSE).