Neural Networks For Your Dog
Learn to build neural networks from scratch in Python, covering perceptrons, gradient descent, and deep learning concepts through simple, engaging explanations and hands-on coding.
Reproducing GPT-2 (124M) from Scratch - Implementation and Optimization
Comprehensive tutorial on reproducing GPT-2 (124M) from scratch, covering implementation, optimization, training setup, and results analysis. Includes practical coding and performance tuning tips.
LLMs Are Not Black Magic - Understanding Neural Networks and Generative AI
Demystifying LLMs and AI: A concise explanation of neural networks, image recognition, text processing, and GPT models, revealing the non-magical nature of these technologies.
Audio-Visual Self-Supervised Learning: Insights from Infant Development
Explore how neural networks learn audio-visual representations from video streams, mimicking infant learning through synchronization of sight and sound.
Explorations in Exploration: Deep Learning Meets Value of Information for Sequential Experimental Design
Exploring machine learning's role in sequential experimental design, focusing on quantifying information value and improving flexibility in planning future experiments.
Why AI is Unpredictable
Explore AI's unpredictability through amusing analogies and expert insights. Gain a thought-provoking perspective on the challenges and implications of artificial intelligence's inherent unpredictability.
Nightshade: Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models - Session 335
Explore poisoning attacks on text-to-image models, focusing on the Nightshade technique's ability to manipulate AI-generated images through targeted data manipulation.
Fireside Chat on PyTorch and Machine Learning
Insightful discussion on PyTorch's development, AI trends, and the future of machine learning with industry experts Soumith Chintala and Merve Noyan.
NN-Defined Modulator - Reconfigurable and Portable Software Modulator for IoT Gateways
Innovative approach using neural networks for IoT gateway modulators, offering improved extensibility and portability across diverse hardware platforms with enhanced efficiency.
Brain-on-Switch: Advanced Intelligent Network Data Plane via NN-Driven Traffic Analysis
Innovative approach to enable neural network-driven traffic analysis at line-speed in programmable networks, overcoming limitations of tree-based models and enhancing intelligent network data plane capabilities.
THC - Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression
Accelerates distributed deep learning with Tensor Homomorphic Compression, enabling direct aggregation of compressed values and compatibility with in-network aggregation for faster training of vision and language models.
The Fundamentals of Modern Deep Learning with PyTorch
Learn PyTorch for deep learning: train neural networks for image and text classification, explore tensor operations, automatic differentiation, and modern libraries like PyTorch Lightning for efficient GPU training.
Real-World PyTorch: From Zero to Hero in Deep Learning and LLMs - Tensors, Operations, Model Training
Comprehensive PyTorch tutorial covering tensors, operations, GPU usage, datasets, neural networks, and model training. Hands-on examples for mastering deep learning and LLMs.
Using RunPod Storage Network Volume with Automatic1111 and ControlNet - Advanced Tutorial
Comprehensive guide on using RunPod's Storage Network Volume, deploying Automatic1111 with ControlNet, and leveraging InstantID for advanced image generation and face transfer techniques.
Geometric Deep Learning - Graph Neural Networks and Differential Equations
Explore Graph Neural Networks, symmetry principles, and connections to differential equations, geometry, and topology in this comprehensive introduction to Geometric Deep Learning.
How Connections Build Intelligence - Human and Artificial
Explore the fundamental role of connections in building intelligence, both in human brains and artificial systems, with insights from AI entrepreneur Nigel Toon on information processing and knowledge creation.
Visual Introduction to Transformers and GPTs - Deep Learning Chapter 5
Visual introduction to transformers and GPTs, covering key concepts like word embeddings, deep learning premise, and softmax. Explores the inner workings of these models with clear animations and explanations.
The Most Important Algorithm in Machine Learning - Backpropagation Explained
Explore backpropagation's fundamentals, from curve fitting to gradient descent, chain rule, and computational graphs. Gain insights into this crucial machine learning algorithm's principles and applications.
Get to Know PyTorch - A Cutting Edge Open Source AI Framework for Deep Learning
Explore PyTorch, a leading open-source AI framework. Learn deep learning fundamentals, PyTorch basics, and recent developments. Discover how to contribute and leverage PyTorch for creating neural network models.
Medical Melanoma Detection - TensorFlow U-Net Tutorial
Step-by-step guide to implementing a U-Net model for melanoma detection using TensorFlow/Keras, covering data preparation, augmentation, model building, training, testing, and result visualization.
DenseNet Deep Neural Network Architecture Explained
Comprehensive explanation of DenseNet architecture, including its benefits and implementation in PyTorch. Covers theory, results, and practical coding walkthrough for deep learning enthusiasts.