Support Vector Machine - SVM - Machine Learning Tutorial
Support Vector Machines have various applications such as they can be used in classification of images, in handwritten character recognition, classification of satellite SAR data. Learn about SVM in this video by Great Learning.
Practical Deep Learning for Coders 2019
Comprehensive deep learning course covering image classification, NLP, tabular data, and advanced topics. Includes hands-on coding and ethical considerations.
Azure Percept - AI IoT Edge Made Easy - Part 1
Explore Azure Percept DK for IoT edge AI: hardware overview, model building, and deployment demos. Hands-on tutorials for object detection and bird classification using Azure Percept Studio.
Automate Custom Vision Model Creation with AutoML for Images
Learn to automate custom vision model creation using AutoML for Images in Azure ML. Explore real-world applications in quality control, retail, and fire detection with expert guidance.
Neural Networks Examples in MATLAB
Explore practical applications of neural networks in MATLAB, including image processing, classification, and prediction tasks using various deep learning architectures.
Introduction to Convolutional Neural Networks with TensorFlow
Learn to build and implement convolutional neural networks for image classification using TensorFlow. Gain hands-on experience in deep learning techniques for computer vision tasks.
Artificial Intelligence Tutorial for Beginners - What Is AI?
Comprehensive introduction to AI, covering neural networks, NLP, and computer vision. Explores key concepts, applications, and real-world use cases for beginners entering the field of artificial intelligence.
Introduction to Transfer Learning
Explore transfer learning to adapt pre-trained networks for microscopy applications, enhancing accuracy with limited labeled data and reducing training time.
Beyond Deep Learning - Learning+Reasoning
Explore advanced AI concepts beyond deep learning, focusing on integrating reasoning with learning for more robust and interpretable systems in this IBM Research lecture.
Getting Closer to Human Intelligence Through Robotics
Explore how robotics research can advance AI towards human-level intelligence by relaxing current assumptions and focusing on physical interaction and broader capabilities.
Re-Imagining the Social Sciences in the Age of AI - March 4, 2020
Explore the intersection of AI and social sciences through expert talks on mate selection decision-making and human behavior as AI's next frontier, followed by a moderated discussion and audience Q&A.
The Carbonate Forum 2021 - Artificial Intelligence in Carbonates
Explore AI applications in carbonate geology, covering microcrystal segmentation and CNN architectures for core classification. Gain insights into cutting-edge techniques and their geological implications.
From the Past to Satellites - New Ways of Mapping Fossils from Remote Locations
Innovative satellite imaging techniques for fossil discovery and preservation in remote locations, enhancing paleontological fieldwork efficiency and specimen recovery.
TensorFlow js en Espaol
Aprende inteligencia artificial con TensorFlow.js: crea aplicaciones web que reconocen imágenes, sin instalaciones ni configuraciones complejas. Ideal para principiantes en IA y desarrollo web.
Handwritten Digit Recognition on MNIST Dataset - Machine Learning Tutorial
Aprenda a reconocer dígitos escritos a mano utilizando el conjunto de datos MNIST y técnicas de aprendizaje automático en Python, con explicaciones en hindi.
IA Aplicada con Redes Neuronales de Convolución para Automatización Industrial
Explora la aplicación de redes neuronales convolucionales en automatización industrial, incluyendo simulación de selección de objetos con actuadores y aspectos teórico-prácticos de implementación.
LLMOps: Personalizar ViT Classifier con tu Propia Data y Docker Inference
Personaliza un Vision Transformer con tu dataset, crea un docker y un punto de inferencia con FastAPI para clasificación de imágenes.
LLMOps: Inferencia de Clasificador ViT Fine-Tuned en CPU con C#
Aprende a realizar inferencia en C# con un Vision Transformer personalizado en formato ONNX utilizando CPU para clasificación de imágenes.
LLMOps: Converting Fine-Tuned ViT Classifier to ONNX for CPU Inference
Convierte un Vision Transformer personalizado a ONNX y realiza inferencia en CPU, optimizando el rendimiento del modelo de clasificación de imágenes.
Fine-Tuning ViT Classifier for Retinal Image Detection - Part 2 (Español)
Personaliza un Vision Transformer para clasificar imágenes de retina, detectando ojos enfermos usando el dataset EyeQ. Aprende a ajustar modelos pre-entrenados para tareas específicas.
Microsoft AI: MLNet Framework en C# - Transfer Learning para Clasificación de Imágenes
Integra MLNet con TensorFlow para clasificar imágenes de superficies de cemento mediante transfer learning y la API de ML.NET Image Classification Library.