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Deep Learning with Rust:: Linear Algebra, Tensor Operations, and High-Performance Neural Network Engineering
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- I remember the exact moment I realized I didn't really understand how AI worked. Sure, I could import a Python library and train a model in five lines of code. But what was actually happening beneath the surface? When the loss curve inexplicably flatlined, or the GPU suddenly ran out of memory, I was completely blind.You've probably felt that exact same frustration.The black box of modern machine learning keeps you dependent on pre-packaged tools and limits your ability to innovate. I wrote this book to shatter that box. I’ll walk you down to the bare silicon, showing you exactly how to engineer the calculus, manipulate the memory, and command the hardware. By the time we are done, you won't just be an AI user—you will be an AI architect.What's insideThe Foundation: Engineer a custom Automatic Differentiation (Autograd) engine and manage multidimensional tensor memory.Advanced Architecture: Construct Convolutional networks for vision, LSTMs for time-series, and a complete GPT-style Transformer block from the ground up.Hardware Supremacy: Break the CPU bottleneck by writing custom GPU assembly (PTX) and bridging Rust directly to CUDA and cross-platform WebGPU.Edge Deployment: Strip away training overhead, compress your model weights into INT8, and build a blazing-fast Key-Value (KV) cache for autoregressive text generation.Zero-Trust Security: Cryptographically sign your ONNX models, build dynamic batching queues, and lock down your inference pipeline against supply-chain attacks.Who it's meant forThis book is not a quick Python tutorial. It is written for software developers, systems engineers, and ambitious data scientists who are tired of high-level abstractions. If you have a working knowledge of Rust and a basic grasp of calculus, and you want to truly understand the physics of artificial intelligence, this book is designed exactly for you.The AI revolution will not be led by people who only know how to import a library; it will be led by the engineers who know how to build the engine. Stop trusting the black box. Grab your copy today, fire up your compiler, and let’s engineer intelligence from bare metal.
| Publication date | May 14, 2026 |
| Language | English |
| File size | 2.7 MB |
| Screen Reader | Supported |
| Enhanced typesetting | Enabled |
| X-Ray | Not Enabled |
| Word Wise | Not Enabled |
| Print length | 300 pages |
| Page Flip | Enabled |
| Item Weight | 1.5 lbs (680 grams) |
Product Description
Deep Learning with Rust:: Linear Algebra, Tensor Operations, and High-Performance Neural Network Engineering
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