Enhancing Old Videos to Full HD Using AI Tools - Video Restoration Tutorial
Discover how to transform old, low-quality videos into full HD using AI-powered video enhancement tools, Python libraries, and GPU processing for superior resolution and clarity.
Jingdong Algorithm Debug System - StarGazing Introduction
Discover how to effectively debug algorithms using Jingdong's StarGazing system, exploring its features and implementation in large-scale AI development environments.
Deep learning ด้วย tensorflow และ keras
เรียนรู้การสร้างโมเดล Deep Learning ด้วย TensorFlow และ Keras ตั้งแต่พื้นฐานจนถึงระดับสูง ครอบคลุมการติดตั้ง การใช้งาน และเทคนิคการปรับแต่งโมเดล
TensorFlow Tutorials 神经网络 教学 教程
从零开始学习TensorFlow构建神经网络，涵盖基础概念、CNN、RNN等高级主题，通过实例和可视化深入理解深度学习原理和应用。
Formation Tensorflow 2.0
Apprenez les fondamentaux de TensorFlow 2.0, des perceptrons aux réseaux de neurones récurrents, en passant par la normalisation des données et la création de modèles personnalisés.
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.
TensorFlow Machine Learning Basic Tutorial
TensorFlow와 머신러닝의 기초를 배우고 실제 프로젝트로 배추 가격 예측 AI를 개발하는 과정. 개발환경 설정부터 선형 회귀, K-평균 알고리즘, 데이터 시각화, 웹 서버 구현까지 다룹니다.
Tensorflow.js
TensorFlow.js를 활용한 AI 개발: 모델 생성, 학습, 활용 및 딥러닝 기초를 다루는 실용적인 JavaScript 기반 AI 프로그래밍 입문 과정
Tensorflow Tutorial for Beginner in Python - Hindi
हिंदी में TensorFlow की शुरुआत से लेकर उन्नत अवधारणाओं तक का व्यापक प्रशिक्षण, जिसमें न्यूरल नेटवर्क, रिग्रेशन, वर्गीकरण और CNN शामिल हैं।
Develop, Build and Deploy Lightweight AI Services with WebAssembly
使用WebAssembly开发轻量级AI服务,实现高效推理。学习创建PyTorch和TensorFlow函数,扩展大语言模型,以及使用K8s等工具进行部署。
Machine Intelligence at Google Scale
Googleの機械学習技術の概要と実用例を紹介。ニューラルネットワークやディープラーニングの基礎から、GoogleのAIサービスやクラウド製品の活用方法まで解説。
Proyecto Centinela: Seguridad en el Hogar Usando Raspberry Pi y Tensorflow
Proyecto Centinela: sistema de seguridad personalizado con Raspberry Pi y TensorFlow. Reconocimiento facial, almacenamiento local, alertas en tiempo real y integración con dispositivos inteligentes para mayor control y privacidad.
MLOps MLflow: Deep Learning Frameworks PyTorch and TensorFlow in MLflow - Spanish
Aprende a integrar Tensorflow y Pytorch con MLflow para optimizar tus proyectos de Deep Learning y mejorar el seguimiento de experimentos.
LLMOps: Como usar Nvidia TensorRT SDK para Inferencia en GPU
Optimiza la inferencia en GPU con Nvidia TensorRT SDK, convirtiendo modelos y comparando tiempos de ejecución en diferentes precisiones de datos.
LLMOps: Comparación de Openvino, ONNX, TensorRT y Pytorch para Inferencia
Compara el rendimiento de inferencia de modelos convertidos a ONNX, OpenVino y TensorRT frente a PyTorch nativo en GPU y CPU.
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.
NVIDIA Jetson: Enabling AI-Powered Autonomous Machines at Scale
Explore NVIDIA Jetson's AI platform for edge computing in robotics, healthcare, and more. Learn about hardware, software stack, ecosystem, and real-world applications.
Embedded Deep Learning with NVIDIA Jetson
Learn to develop AI and computer vision applications using NVIDIA's deep learning tools. Explore neural network primitives, real-time solutions, and training workflows for intelligent robots and drones on the Jetson Embedded Platform.
Deep Learning Workshop for Satellite Imagery - Training & Prediction
Hands-on deep learning workshop for satellite imagery, covering model training, debugging, prediction, and advanced techniques like custom metrics, heatmaps, and model deployment.
Generative Adversarial Models for Privacy and Fairness
Explore generative adversarial models for enhancing privacy and fairness in machine learning, covering differential privacy, GANs, and real-world applications in data publishing and encoding.
Real-Time Inference of Neural Networks: A Guide for DSP Engineers
Explore real-time neural network inference for DSP engineers. Learn practical steps, compare inference engines, and balance latency, performance, and stability in audio plugin development.