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The Most Complete PyTorch Tutorial You’ve Seen
Everything you need to know to build, train, and scale deep learning models.
AI has now become a necessary skill — no matter what field you’re in, you’ll almost certainly end up using AI in some way. That’s why knowing how to build and train your own neural network model has become an important skill. It might sound intimidating, but in reality most of the underlying work has already been done in modules. For example, as a beginner, you don’t need to know exactly how the computations behind model training work on a CPU versus a GPU — you just need to know which command offloads complex math operations for acceleration. Similarly, training an AI model involves a huge amount of calculus, but you don’t need to write those calculus formulas from scratch either; you can just use the existing built-in functions. In short, you only need to learn how to use these ready-made tools and stack them together like building blocks. This collection of tools is called a “framework.”
AI is a broad field, and within it, the technique that lets machines find patterns in data is called Machine Learning (ML). What this article will teach is the core branch of ML — Deep Learning (DL). Deep learning specifically uses “neural networks” to solve problems. There are many frameworks in the deep learning space, and…
