Coursera 笔记

Module 03 · Sequence Models & Attention Mechanism

Neural Machine Translation神经机器翻译

Programming Assignment: Neural Machine Translation 编程作业:神经机器翻译

You have not submitted. You must earn 80/100 points to pass. 您尚未提交。您必须获得 80/100 分才能通过。

Deadline 截止日期

Pass this assignment by Jan 19, 11:59 PM CST
请于 1 月 19 日前提交此作业,截止时间为美中时间晚上 11:59

Welcome to your first programming assignment for this week!
欢迎来到本周的第一个编程作业!

  • You will build a Neural Machine Translation (NMT) model to translate human-readable dates ("25th of June, 2009") into machine-readable dates ("2009-06-25").
    您将构建一个神经机器翻译(NMT)模型,将可读日期(“2009 年 6 月 25 日”)翻译为机器可读日期(“2009-06-25”)。
  • You will do this using an attention model, one of the most sophisticated sequence-to-sequence models.
    您将使用注意力模型来完成这项任务,这是最复杂的序列到序列模型之一。

This notebook was produced together with NVIDIA's Deep Learning Institute.
本笔记本与 NVIDIA 深度学习学院共同制作。

📎 Neural_machine_translation_with_attention_v4a-713f81bc-563f-45cd-a4e3-175f932624a7.ipynb

Source: https://www.coursera.org/learn/nlp-sequence-models/programming/L0BBe/neural-machine-translation