Course Outline


  • Why Neural Machine Translation?

Overview of the Torch Project

Installation and Setup

Preprocessing Your Data

Training the Model


Using Pre-Trained Models

Working with Lua Scripts

Using Extensions


Joining the Community

Summary and Conclusion


  • Some programming experience is helpful.
  • Experience using the command line.
  • Basic understanding of machine translation concepts.


  • Localization specialists with a technical background
  • Global content managers
  • Localization engineers
  • Software developers in charge of implementing global content solutions
 7 Hours

Number of participants

Price per participant

Related Courses

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

21 Hours

Introduction to Stable Diffusion for Text-to-Image Generation

21 Hours


7 Hours

TensorFlow Lite for Embedded Linux

21 Hours

TensorFlow Lite for Android

21 Hours

TensorFlow Lite for iOS

21 Hours

Tensorflow Lite for Microcontrollers

21 Hours

Deep Learning Neural Networks with Chainer

14 Hours

Distributed Deep Learning with Horovod

7 Hours

Accelerating Deep Learning with FPGA and OpenVINO

35 Hours

Building Deep Learning Models with Apache MXNet

21 Hours

Deep Learning with Keras

21 Hours

Advanced Deep Learning with Keras and Python

14 Hours

Deep Learning for Self Driving Cars

21 Hours

Torch for Machine and Deep Learning

21 Hours

Related Categories