Explores Andrej Karpathy's concept of Software 2.0, where AI writes programs through objectives and gradient descent, focusing on task verifiability.
A course teaching how to code Large Language Models (LLMs) from scratch to deeply understand their inner workings and fundamentals.
Strategies for improving LLM performance through dataset-centric fine-tuning, focusing on instruction datasets rather than model architecture changes.
A guide to participating in the NeurIPS 2023 LLM Efficiency Challenge, focusing on efficient fine-tuning of large language models on a single GPU.
A technical guide to coding the self-attention mechanism from scratch, as used in transformers and large language models.
Argues that AI image generation won't replace human artists, using information theory to explain their unique creative value.
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.
Author announces the launch of 'Ahead of AI', a monthly newsletter covering AI trends, educational content, and personal updates on machine learning projects.
Challenges the common practice of using powers of 2 for neural network batch sizes, examining the theory and practical benchmarks.
A hands-on review of PyTorch's new M1 GPU support, including installation steps and performance benchmarks for deep learning tasks.
Author announces a new machine learning book covering scikit-learn, deep learning with PyTorch, neural networks, and reinforcement learning.
A comprehensive deep learning course covering fundamentals, neural networks, computer vision, and generative models using PyTorch.
A review of the book 'Deep Learning with PyTorch', covering its structure, content, and suitability for students and beginners in deep learning.
Explores the visual similarities between images generated by neural networks and human experiences in dreams or under psychedelics.
A blog post exploring the parallels and differences between human cognition and machine learning, including biases and inspirations.
An overview of tools and techniques for creating clear and insightful diagrams to visualize complex neural network architectures.
Research on using semi-adversarial neural networks to generate gender-neutral face images, enhancing privacy while preserving biometric utility.
A tutorial on implementing a neural network in JavaScript using Google's deeplearn.js library to improve web accessibility by choosing font colors.
An overview of Machine Learning applications in Remote Sensing, covering key algorithms and the typical workflow for data analysis.
A guide for beginners on how to start learning deep learning using the Keras library, including recommended resources and prerequisites.
