PyTorch Foundation - One Year of Open Governance and Future Directions
Explore PyTorch Foundation's first year: growth, achievements, and future plans. Learn about community expansion, key releases, and the foundation's role in advancing open-source AI technologies.
End-to-End Deep Learning Project: Kidney Disease Classification with MLflow, DVC, and Deployment
Comprehensive deep learning project on kidney disease classification, covering data ingestion, model preparation, training, evaluation, MLflow integration, DVC pipeline, and AWS deployment.
Build Your First PyTorch Model - Image Classification Tutorial
Learn to build an image-classifying PyTorch model for playing cards in this hands-on tutorial. Covers datasets, model creation, training, and result analysis.
Machine Learning and Side-Channel Analysis - Part 2
Explore advanced machine learning techniques for side-channel analysis in cryptography, covering neural networks, deep learning, and collision attacks with practical applications and sensitivity analysis.
Streaming for LangChain Agents and FastAPI
Learn to implement streaming for LangChain Agents and serve it through FastAPI, covering basics to advanced techniques for efficient LLM integration and deployment.
Creating Hidden AI Art with Stable Diffusion - QR Codes and Deep Object Placement
Learn to create stunning AI-generated hidden art using Stable Diffusion, including QR codes and deep object placement. Master techniques for embedding images within patterns for unique, visually captivating results.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 9
Explore advanced machine learning techniques for high energy physics: Deepsets, Graph Neural Networks, and Transformers. Gain insights into cutting-edge data analysis methods for particle physics research.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 4
Explore advanced machine learning techniques for high energy physics, including Deepsets, Graph Neural Networks, and Transformers, with expert Sanmay Ganguly.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 1
Explore advanced machine learning techniques for high-energy physics, including Deepsets, Graph Neural Networks, and Transformers, with expert Sanmay Ganguly.
Hot Chips, AI Exploitation, and Supercomputers - Weekly AI News Roundup
Explore global chip wars, AI labor exploitation concerns, and supercomputer advancements. Discuss deepfakes in Diwali celebrations and enjoy AI-inspired music remix. Stay informed on key AI developments and their potential impacts.
Machine Learning for LHC Theory - Lecture 2
Explore advanced machine learning techniques for Large Hadron Collider theory, focusing on statistical methods and their applications in high-energy physics research.
TinyRL: Teaching AI to Swing Up a Real Pendulum
Explore reinforcement learning to train an AI agent to swing up a real pendulum using Arduino, Python frameworks, and ESP32 deployment, with practical demonstrations and troubleshooting tips.
The Future of Generative AI - Possibilities and Challenges
Explore the future of generative AI with Professor Michael Wooldridge, covering its capabilities, challenges, and potential impact on society. Gain insights into machine learning, neural networks, and the evolution of AI technology.
Artificial Intelligence and Machine Learning - Keynote Panel
Explore AI and machine learning insights from industry leaders, covering advancements, applications, and future trends in technology and business.
Running Distributed TensorFlow on DC/OS
Learn to run distributed TensorFlow on DC/OS, addressing challenges in large-scale machine learning. Explore framework design, live demo, and practical implementation for efficient model training on your infrastructure.
AI Art Course Install and Setup - Automatic1111 and Stable Diffusion
Learn to set up Automatic1111 UI and Stable Diffusion for AI art creation. Hands-on approach with project-based learning to explore image generation using artificial intelligence.
CNN Confusion Matrix with PyTorch - Neural Network Programming
Learn to build, plot, and interpret a confusion matrix using PyTorch for neural network evaluation, including techniques for disabling gradient tracking and analyzing model performance across different classes.
CNN Training Loop Explained - Neural Network Code Project
Learn to build a convolutional neural network training loop using Python and PyTorch. Gain practical skills in implementing deep learning algorithms for image processing tasks.
CNN Weights - Learnable Parameters in PyTorch Neural Networks
Explore PyTorch's inner workings, including OOP concepts, convolutional and linear layer weight tensors, and matrix multiplication for deep learning in neural networks.
Build PyTorch CNN - Object-Oriented Neural Networks
Learn to build a convolutional neural network using PyTorch for computer vision and AI applications. Gain hands-on experience in implementing object-oriented neural network architectures.
A Sockets API for LoRa - Standardizing IoT Network Interfaces
Explore a proposed Linux sockets API for LoRa, enabling standardized software interfaces for IoT modules. Learn about kernel integration, device drivers, and network protocols.