SMDL

Sequence Modeling with Deep Learning Lessons and Workshops

For this course we will be using PyCharm as the Integrated Development Environment (IDE).

1. Download and install Anaconda for Python 3.8: https://www.anaconda.com/products/individual

2. Download and install PyCharm Community Edition: https://www.jetbrains.com/pycharm/download

3. Follow the steps in the setup video: https://youtu.be/d9aotUJenWY

• Installing the EduTools plugin
• Importing the Course lessons and code from Releases.

Intro Videos

• Setting up EduTools: https://youtu.be/d9aotUJenWY
• Debugging in PyCharm: https://youtu.be/y4bUDHMJZFE
• Training an end-to-end model and calling it from Flask: https://youtu.be/w4dj3MfjM-8
• Debugging a Flask app: https://youtu.be/ahlBohYUMq4

Modules

Each module contains lessons to cover the building blocks, under the lessons folder. After going through the lessons, you can then apply the building blocks to train the model in the train folder, and call the trained model from a flask application in the app folder. Refer to the README.md files in each day's lessons.

• Day 1: Sentiment Classification: https://github.com/lisaong/adl/tree/master/SMDL/Day1
• Day 2: Chat Reply Generation: https://github.com/lisaong/adl/tree/master/SMDL/Day2
• Day 3: Neural Machine Translation: https://github.com/lisaong/adl/tree/master/SMDL/Day3
• Day 4: Video Action Classification: https://github.com/lisaong/adl/tree/master/SMDL/Day4
• Day 5: Attention and Transformer: https://github.com/lisaong/adl/tree/master/SMDL/Day5

Documentation

• EduTools plugin for PyCharm: https://www.jetbrains.com/help/education/install-edutools-plugin.html?section=PyCharm#72cb