Plan Szkolenia

Introduction

Understanding Hardware Accelerated Decoding Methods

Overview of NVidia DeepStream SDK

Setting up the Development Environment

Preparing a Video Feed

Processing a Video Feed

Training a Deep Learning Model

How Transfer Learning Works

Improving the Model's Accuracy Through Transfer Learning

Developing a Neural Network Model to Track Moving Objects

Running a Video Analytics Inference Engine

Deploying the Inference Engine

Integrating a Deep Learning Model with an Application

Deploying an Intelligent Video Analytics (IVA) Application

Monitoring the Application

Optimizing the Inference Engine and Application

Troubleshooting

Summary and Conclusion

Wymagania

  • An understanding of deep neural networks
  • Python and C programming experience

Audience

  • Developers
  • Data scientists
 14 godzin

Liczba uczestników



Cena za uczestnika

Opinie uczestników (2)

Szkolenia Powiązane

Administration of CUDA

35 godzin

GPU Programming with CUDA and Python

14 godzin

Computer Vision with OpenCV

28 godzin

Python and Deep Learning with OpenCV 4

14 godzin

Raspberry Pi + OpenCV for Facial Recognition

21 godzin

Pattern Matching

14 godzin

Advanced Stable Diffusion: Deep Learning for Text-to-Image Generation

21 godzin

Introduction to Stable Diffusion for Text-to-Image Generation

21 godzin

AlphaFold

7 godzin

TensorFlow Lite for Embedded Linux

21 godzin

TensorFlow Lite for Android

21 godzin

TensorFlow Lite for iOS

21 godzin

Tensorflow Lite for Microcontrollers

21 godzin

Deep Learning Neural Networks with Chainer

14 godzin

Distributed Deep Learning with Horovod

7 godzin

Powiązane Kategorie