Advance Deep Learning Workshop for Satellite Imagery - Model Export & Production
Hands-on workshop on advanced deep learning techniques for satellite imagery, covering remote debugging, model deployment, activation heatmaps, and custom predictions using TensorFlow and Keras.
Hands-on Coding Lab: Text Prompt UI for Stable Diffusion Models - Part 4
Learn to save and retrieve prompts and images for Stable Diffusion models using Gradio. Implement a UI with dropdown lists, JSON storage, and duplication prevention for efficient prompt management.
Hands-on Coding Lab: Text Prompt UI for Stable Diffusion Models - Part 3
Learn to create a Python Gradio UI for Stable Diffusion models, including audio-to-text prompts, prompt updates, and image saving functionality in this hands-on coding tutorial.
A Developer Guide to Use Stable Diffusion Text-to-Image AI Model in Python
Learn to implement Stable Diffusion text-to-image AI model in Python, covering setup, pipeline creation, model testing, and Gradio app development for both local and Google Colab environments.
Run Stable Diffusion on Any Device - No PC Required
Learn to create AI images using Stable Diffusion on rented remote computers. Step-by-step guide for setup, installation, and using ControlNet for AI animations without expensive hardware.
ControlNET Posing Tools - Complete Guide for Stable Diffusion
Comprehensive guide to ControlNET posing tools for Stable Diffusion, covering OpenPose Editor, Posemaniacs, Posemy.Art, and Daz3D. Includes tips and tricks for creating perfect poses.
LORA with ControlNET - Get the Best Results - Complete Guide
Comprehensive guide on optimizing LORA with ControlNET in Stable Diffusion, covering models, settings, and techniques for achieving superior AI-generated images.
Stable Diffusion 1.5 - Install, Comparison, Guide - Everything You Need to Know
Comprehensive guide on installing, comparing, and using Stable Diffusion 1.5, including inpainting features and performance comparisons with version 1.4.
Multi-Scale Multi-Band DenseNets for Audio Source Separation
Explore multi-scale multi-band DenseNets for audio source separation, featuring innovative architecture with up-sampling, block skip connection, and band-dedicated dense blocks to improve performance and efficiency.
DF-GAN: Deep Fusion Generative Adversarial Networks for Text-to-Image Synthesis
Learn about DF-GAN, a deep fusion architecture for text-to-image synthesis. Explore its simplified backbone, gradient penalty, and deep fusion block, with quantitative and qualitative results.
Deep Bayesian Bandits - Exploring in Online Personalized Recommendations
Explore online personalized recommendations using Deep Bayesian Bandits. Learn about UCB, Thompson Sampling, and innovative approaches like bootstrapping and dropout methods for effective exploration strategies.
Deploying Optimized Deep Learning Pipelines
Survey of deep learning pipeline optimization techniques, exploring quantization, distillation, and math library selection. Discusses trade-offs for deployment and provides insights for efficient ML implementation.
Scaling AI Applications with Ray - Richard Liaw & Eric Liang | ODSC East 2019
Explore Ray, a distributed execution engine for AI workloads. Learn about Tune for hyperparameter optimization and RLib for reinforcement learning, with insights on scalability and practical applications.
CNN Explainer - Learning Convolutional Neural Networks with Interactive Visualization
Interactive visualization tool for understanding convolutional neural networks, covering layers, filters, padding, activation, and pooling. Enhances learning through hands-on exploration.
Efficient Distributed Deep Learning Using MXNet
Explore distributed deep learning with MXNet, covering practical challenges, deployment strategies, and advanced techniques for efficient large-scale machine learning implementations.
Unsupervised Representation Learning
Explore hierarchical representation learning, common sense AI, and advanced neural network architectures with Yann LeCun. Gain insights into unsupervised learning and video prediction techniques.
Deep Learning in Bioinformatics - Recent Advancement
Explore recent advancements in deep learning for bioinformatics, covering BTINET, autoencoders, and deep belief networks. Gain insights into cutting-edge applications in genomics, drug discovery, and disease prediction.
Word Embedding with Keras - A RStudio Tutorial
Learn word embedding techniques using Keras in RStudio. Covers theory, concepts, and practical implementation, including Keras basics and machine learning fundamentals for natural language processing.
Deep Generative Models and Stable Diffusion: Revolution in Visual Synthesis - Lecture by Björn Ommer
Explore deep generative models, focusing on diffusion models and Stable Diffusion. Learn about visual synthesis advancements, efficiency improvements, and future developments in this cutting-edge field.
Interpreting Deep Generative Models for Interactive AI Content Creation
Explore deep generative models for AI content creation, covering image generation, latent space manipulation, and interactive techniques. Learn about challenges and applications in this cutting-edge field.
Understanding Deep Neural Networks - CVPR 2020 iMLCV Tutorial
Explore deep neural network interpretability through meaningful perturbations, extremal perturbations, and activation analysis. Learn techniques for understanding and improving model behavior in computer vision tasks.