Security of Machine Learning Systems
Explore security challenges in AI and ML systems, including adversarial attacks and MLOps. Learn to apply pen testing skills to ML, with demonstrations on manipulating image recognition and NLP models.
ML On-Device: Building Efficient Models
Explore on-device machine learning for efficient, privacy-preserving models on mobile and edge devices. Learn about real-time AI applications, model optimization, and deployment strategies.
Inception V2 Neural Network Architecture Tutorial
Learn advanced deep learning techniques with Inception V2, exploring its architecture and applications in computer vision tasks.
Computer Vision AI Model Building and Deployment with Docker
Build and deploy computer vision AI models quickly using Navan's no-code platform. Learn to create and implement advanced visual recognition systems efficiently.
K8S on the Edge - Arm-based Implementation of Image Recognition
Explore Arm-based image recognition implementation using Kubernetes on edge devices, focusing on practical applications and performance optimization techniques.
GPT-4 Vision: 10 Amazing Use Cases and Applications
Explore 10 innovative applications of GPT-4 Vision, from app creation to image analysis, showcasing its versatility and potential in various real-world scenarios.
Input, Processing and Output of Massive Metadata from Image Recognition
Explore reactive computing, streaming ML, and deep learning for image recognition. Learn about serverless architecture and real-time data processing with a live demo of software engineering integration.
Basic Aspects of Convolutional Neural Networks - Tutorial
Explore fundamental concepts of convolutional neural networks in this tutorial, covering key principles and applications in deep learning for image processing and pattern recognition.
OpenAI Vision API App Development Tutorial - 1 Hour Challenge
Build an OpenAI Vision API app in this hands-on tutorial, exploring image analysis capabilities and practical implementation techniques.
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.
MLOps: C# Image Recognition with ResNet50v2 Model
Implement image recognition using ResNet50v2 in C# with ONNX and SixLabors.ImageSharp for efficient MLOps workflows.
Raspberry Pi AI Camera - Deep Dive
Explore Raspberry Pi AI Camera capabilities for video data detection and capture. Learn to harness AI for advanced image processing and analysis in your projects.
Faces, Flukes, Fins, and Flanks - How Multispecies Re-ID Models are Transforming Our Approach to AI
Explore how multispecies re-identification models revolutionize AI, enhancing our understanding of animal communication and conservation efforts across diverse species.
The Perception Test - Understanding Higher-Level Intelligence
Explore AI, psychology, and neuroscience perspectives on higher-level intelligence through Viorica Patraucean's insightful discussion of the Perception Test.
Machine Duping - Pwning Deep Learning Systems
Explore vulnerabilities in deep learning systems and learn techniques to manipulate image recognition, speech recognition, and phishing detection through practical demonstrations and attack methodologies.
Some Thoughts on Deep Learning and Infosec - Jeremy Howard - USENIX Enigma - 2018
Exploring the potential of deep learning in infosec, challenging misconceptions and highlighting untapped opportunities for practical applications in cybersecurity.
Tensor Networks and Neural Network States - From Chiral Topological Order to Image Classification
Explore neural networks in quantum physics and image recognition, bridging manybody physics with machine learning for innovative applications in various fields.
Machine Learning Failures - For Art
Explore hilarious machine learning failures in art, from cookie recipes to pony classification, and learn how to deliberately create amusing AI mistakes.
Tensorflow, Deep Learning and Modern Convolutional Neural Nets, Without a PhD
Explore modern convolutional neural networks and deep learning with TensorFlow. Learn practical tips, engineering best practices, and recent advances in image recognition without needing a PhD.
Exploring Deep Learning AI in the Cloud
Explore cloud-based deep learning AI technologies for natural language understanding, speech recognition, image analysis, and text-to-speech. Gain insights into Amazon's AI services and their practical applications.
From 0 to Deep Learning in 3 Hours
Comprehensive introduction to neural networks and deep learning, covering fundamentals, practical applications, and implementation using popular libraries like TensorFlow and Keras.