Shape Inference from Multidimensional Arrays | JavaScript in Hindi | Make Your Own PyTorch #01

Ever wondered how frameworks like PyTorch know the shape of a multidimensional array? In this video, we start building the foundations of our own deep learning framework — from scratch. We’ll implement and understand Shape Inference: how to automatically determine the shape of 1D, 2D, 3D, and N-dimensional array data. 🔥 What You'll Learn What is Shape Inference? How to extract Tensor shape from multidimensional arrays Understanding 1D, 2D, 3D and N-D arrays How nested arrays represent Tensor dimensions How shape is derived from the structure of the data Handling multidimensional JavaScript arrays Building the foundation of a PyTorch-like Tensor Practical implementation in JavaScript This isn't just about writing an array utility. The goal is to understand how the core data structures behind deep learning frameworks work — and gradually Make Your Own PyTorch from scratch. This is the beginning of a journey from: Array → Tensor → Operations → Autograd → Neural Networks → Training All implemented step by step and explained in Hindi. 🚀 Series: Make Your Own PyTorch We are building a deep learning framework from the ground up to understand what happens under the hood instead of treating frameworks as black boxes. If you're interested in PyTorch internals, Tensor implementation, JavaScript, machine learning, or deep learning from scratch, follow the series. #MakeYourOwnPyTorch #PyTorch #DeepLearning #MachineLearning #Tensor #TensorShape #ShapeInference #JavaScript #JavaScriptHindi #DeepLearningFromScratch #MachineLearningHindi #AI #NeuralNetworks #Programming #Coding