Recreate Google Translate - Model Training
Offered By: Edan Meyer via YouTube
Course Description
Overview
Explore the final video in the Neural Machine Translation (NMT) series, focusing on model training and testing for recreating Google Translate. Learn about parameters, training processes, and testing methodologies. Dive into the practical application of concepts covered in previous videos, including NLP models for sequential data, attention mechanisms, self-attention, the mT5 model, and the Hugging Face library for transformers. Witness the recreation of a demo and observe real-time translation tests. Access the GitHub repository, Colab code, and additional resources to deepen your understanding of transformer models and their applications in multilingual machine translation.
Syllabus
Intro
Parameters
Training
Testing
Results
Our App
Taught by
Edan Meyer
Related Courses
Transformers: Text Classification for NLP Using BERTLinkedIn Learning TensorFlow: Working with NLP
LinkedIn Learning TransGAN - Two Transformers Can Make One Strong GAN - Machine Learning Research Paper Explained
Yannic Kilcher via YouTube Nyströmformer- A Nyström-Based Algorithm for Approximating Self-Attention
Yannic Kilcher via YouTube Let's Build GPT - From Scratch, in Code, Spelled Out
Andrej Karpathy via YouTube