A technical comparison of the DGX Spark and Mac Mini M4 Pro for local PyTorch development and LLM inference, including benchmarks.
Compares DGX Spark and Mac Mini for local PyTorch development, focusing on LLM inference and fine-tuning performance benchmarks.
A hands-on guide to understanding and implementing the Qwen3 large language model architecture from scratch using pure PyTorch.
A hands-on tutorial implementing the Qwen3 large language model architecture from scratch using pure PyTorch, explaining its core components.
A tutorial on creating a production-ready Docker image for PyTorch models using Torch Serve, including model archiving and dependency management.
Guide to deploying a low-cost NVIDIA GPU VM on Azure using MSDN credits for PyTorch and TensorFlow machine learning development.
A guide to implementing LoRA and the new DoRA method for efficient model finetuning in PyTorch from scratch.
A technical guide implementing DoRA, a new low-rank adaptation method for efficient model finetuning, from scratch in PyTorch.
Techniques to reduce memory usage by up to 20x when training LLMs and Vision Transformers in PyTorch.
A guide to 9 PyTorch techniques for drastically reducing memory usage when training vision transformers and LLMs, enabling training on consumer hardware.
A tutorial on fine-tuning a BERT model for text classification using the new PyTorch 2.0 framework and the Hugging Face Transformers library.
Learn techniques to speed up PyTorch model training by 8x using PyTorch Lightning, maintaining accuracy while reducing training time.
Techniques to accelerate PyTorch model training by 8x using PyTorch Lightning, with a DistilBERT fine-tuning example.
A comparison of AutoAugment, RandAugment, AugMix, and TrivialAugment image augmentation methods in PyTorch for reducing overfitting.
A comparison of four automatic image augmentation methods (AutoAugment, RandAugment, AugMix, TrivialAugment) in PyTorch for reducing overfitting in deep learning.
A tutorial on fine-tuning a BERT model for text classification using Hugging Face Transformers and Google Cloud TPUs with PyTorch.
A curated list of the top 10 open-source machine learning and AI projects released or updated in 2022, including PyTorch 2.0 and scikit-learn 1.2.
A curated list of the top 10 open-source releases in Machine Learning & AI for 2022, including PyTorch 2.0 and scikit-learn 1.2.
Explains why PyTorch multi-process data loaders cause massive RAM duplication and provides solutions to share dataset memory across processes.
A data scientist reviews his 2022 goals, including technical writing on ML topics and career progression, and sets new goals for 2023.
