Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Overview Strong basics in math, programming, and statistics drive faster AI progressReal projects teach problem-solving better than endless tutorialsData qualit ...

Deep learning has advanced rapidly, driving breakthroughs in image recognition, natural language processing, and autonomous ...

Small. With fp16, our baseline could be trained with only 2GB GPU memory. Friendly. You may use the off-the-shelf options to apply many state-of-the-art tricks in one line. Besides, if you are new to ...

PyTorch Implementation: Build, train, and evaluate a CNN model with detailed steps using the MNIST dataset. Augmentations: Explore the impact of image augmentations on OCR performance. Whether you're ...

Learn how to fine-tune GPT-OSS efficiently with LoRa and quantization. A beginner-friendly guide to optimizing AI models on ...

Nvidia will showcase its Blackwell GPUs, Spectrum-XGS networking, and NVFP4 4-bit AI training breakthroughs at Hot Chips 2025, underscoring its $4.34 trillion dominance in AI chips and growing ...

This article references a detailed tutorial published by blogger LorentzYeung, which guides users step-by-step on how to deploy and fine-tune the GPT-OSS-20Bmodel locally to enhance its multilingual ...

Big Data Technology and Artificial Intelligence are like a pair of "sibling disciplines"—the former provides the fuel (data) for the latter, while the latter imparts wisdom (algorithms) to the former.