Boost Deep Learning Inference Performance with TensorRT | Step-by-Step

Автор: Code With Aarohi

Загружено: 2024-02-21

Просмотров: 12211

Описание: Learn how to increase inference performance for deep learning models using NVIDIA TensorRT!

In this tutorial, we cover:
What TensorRT is and why it’s important for deep learning deployment
How to optimize model inference for NVIDIA GPUs

Benefits of TensorRT: high performance, low latency, memory efficiency, deployment flexibility, and precision control

Real-world applications for TensorRT in autonomous vehicles, robotics, video analytics, and edge AI

Why use TensorRT?
TensorRT allows your models to run faster, more efficiently, and with lower latency, making it perfect for real-time applications. Learn how to leverage its optimizations for PyTorch, TensorFlow, and custom deep learning pipelines.

💬 Queries: Comment below or email [email protected]

#TensorRT #NVIDIA #AI #DeepLearning #ComputerVision #PyTorch #ModelOptimization #InferenceAcceleration #LowLatencyAI #EdgeAI

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Boost Deep Learning Inference Performance with TensorRT | Step-by-Step

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