Poridhi Tensorcode is a hands-on platform built to teach the core of AI/ML: the math, the primitives, and the performance constraints that sit underneath modern frameworks. It’s designed for learners who don’t just want to use models, but want to understand how the building blocks work: tensors, kernels, memory, and the operations that decide speed and cost. (tensorcode.poridhi.io)

At the center of the platform is a GPU-enabled CUDA/Triton playground where users can write and run kernels, experiment with GPU-accelerated programs, and develop intuition about performance trade-offs. Alongside that, Tensorcode offers interactive problem sets, including LeetCode-style exercises for AI/ML reasoning and GPU programming, that push learners to implement core operations rather than only calling library APIs.

Tensorcode also supports progressive framework learning (e.g., PyTorch, NumPy) through practice-driven content: syntax drills, implementation exercises, and guided patterns that connect fundamentals to real systems work. Interactive docs and game-like modules help learners stay engaged while still doing serious technical practice—especially for topics that are usually taught too abstractly.