- Applied Machine Learning
- Model Deployment
- Tensorflow
- Performance Tuning
- Convolutional Neural Networks
- Deep Learning
- Keras (Neural Network Library)
- Python Programming
Optimize TensorFlow Models For Deployment with TensorRT
Completed by Yilber Alberto Rojas
October 1, 2020
2 hours (approximately)
Yilber Alberto Rojas's account is verified. Coursera certifies their successful completion of Optimize TensorFlow Models For Deployment with TensorRT
What you will learn
Optimize Tensorflow models using TensorRT (TF-TRT)
Use TF-TRT to optimize several deep learning models at FP32, FP16, and INT8 precision
Observe how tuning TF-TRT parameters affects performance and inference throughput
Skills you will gain
