Скачать или смотреть 🚀 PyTorch Tensors Explained from Scratch Scalars, Vectors, Matrices & Beyond 🔥

Tensors are the core building blocks of deep learning 🧠—and mastering them is essential if you want to work confidently with PyTorch, neural networks, and AI models.

In this video, we take a clear, visual, and practical approach to understanding PyTorch tensors, starting from absolute basics and smoothly progressing to more advanced concepts 🚀.

🔍 What you’ll learn in this video:

✅ What a tensor really is (explained intuitively)
✅ Difference between Scalar (0D), Vector (1D), Matrix (2D), and Tensor (3D+)
✅ How tensor shapes & dimensions work in PyTorch
✅ Hands-on PyTorch code examples with real outputs
✅ How tensors relate to NumPy arrays
✅ Why tensors are critical for deep learning & GPU acceleration ⚡

Whether you are:
👶 A beginner starting with PyTorch
👨‍💻 A developer transitioning from NumPy
🧠 Or a professional refreshing core ML concepts

This video gives you a solid foundation you can build on for:

Deep Learning

Computer Vision

NLP

Model Training & Optimization

💡 By the end of this video, tensors will feel simple, logical, and powerful.

👉 Don’t forget to like 👍, subscribe 🔔, and share if this helped you!

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