Project: Machine Translation
Instructions
This project requires GPU acceleration to run efficiently. Please refer to the instructions below to complete the project.
Option 1: Udacity Workspaces with GPU Support (Highly Recommended)
Open the NLP Machine Translation Workspace]( https://classroom.udacity.com/nanodegrees/nd892/parts/94230570-1456-442c-a152-ca4e171acbfc/modules/162cd048-bbff-412e-8f14-29c34cc2c960/lessons/30f31cf9-74bd-4764-a223-ea2967820ac7/concepts/b7226898-22d9-46ea-bafc-28f166c632ea ) lesson above and complete the project.
Option 2: AWS EC2 (Recommended - but more difficult than Workspaces)
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Follow the Udacity instructions to launch an EC2 GPU instance . All of the remaining instructions should be executed in the EC2 instance.
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Clone the project GitHub repository, and navigate to the downloaded folder:
git clone https://github.com/udacity/aind2-nlp-capstone
cd aind2-nlp-capstone
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Start Jupyter:
jupyter notebook --ip=0.0.0.0 --no-browser -
Look at the output in the window, and find the line that looks like the following:
Copy/paste this URL into your browser when you connect for the first time to login with a token:
http://0.0.0.0:8888/?token=3156e...
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Copy and paste the complete URL into the address bar of a web browser (Firefox, Safari, Chrome, etc). Before navigating to the URL, replace
0.0.0.0in the URL with the "IPv4 Public IP" address from the EC2 Dashboard. Press Enter. -
Click on machine_translation.ipynb . Follow the instructions in the notebook.
Option 3: Running on your Local Machine (NOT Recommended)
- Clone the repository, and navigate to the downloaded folder.
git clone https://github.com/udacity/aind2-nlp-capstone
cd aind2-nlp-capstone
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Create (and activate) a new environment with Python 3.5 and the
numpypackage.
conda create --name aind-nlp-capstone python=3.5 numpy
source activate aind-nlp-capstone
- Install/Update TensorFlow.
pip install tensorflow==1.1 -U
- Install/Update Keras.
pip install keras -U
- Switch Keras backend to TensorFlow.
KERAS_BACKEND=tensorflow python -c "from keras import backend"
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Start Jupyter:
jupyter notebook --no-browser - Look at the output in the window, and find the line that looks like the following:
Copy/paste this URL into your browser when you connect for the first time to login with a token:
http://0.0.0.0:8888/?token=3156e...
-
Copy and paste the complete URL into the address bar of a web browser (Firefox, Safari, Chrome, etc). Press Enter.
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Click on machine_translation.ipynb . Follow the instructions in the notebook.
Submission
Follow the instructions in the notebook to submit your project.
Project Submission Checklist
Before submitting your project, please review and confirm the following items.
I am confident all rubric items have been met and my project will pass as submitted.
Project builds correctly without errors and runs.
All required functionality exists and my project behaves as expected per the project's specifications.
Once you have checked all these items, you are ready to submit!