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This page presents helpful resources to ramp yourselves up on Python, React, AWS, and any other frameworks we use in our stack. If you come across any helpful resources, please put them here
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"This course was what got me started in Python. This course is a masterpiece in my opinion for introducing Python in an accessible manner. Check out Python For Everybody Textbook. You will really want to focus on chapters 2-10, 13-14 to get a good foundation for Python" - Karthik Subramanian
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"The all-knowing truth about Pytorch for DLP: Pytorch Official Docs"
- "A friend actually helped me get started on React and I did a tutorial on freeCodeCamp. But I'd say this video simplifies it best, going through the basics of React, useState, useEffect, and useRef (less important): Learn React in 30 Minutes" - Faris Durrani
- "A nice brief and concise video on why we use AWS in DLP: AWS in 10 Minutes" - Karthik Subramanian
To understand our AWS deployment, it's important to have a good understanding of Docker. At Georgia Tech, you'd take a class called CS 2110 (Computer Organization and Programming) and will interact with Docker. Docker is not something to be afraid of. It's not a very difficult concept to understand and it's very important in our project.
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What is Docker in 5 Minutes. "Really good intro to Docker and the code examples provided in the video are nice accompaniments to the concepts" - Karthik Subramanian
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"What the Heck is Docker and why care about it?". Helpful article written by TAs at Georgia Tech. put link here @faris
- Home
- Terraform
- Bearer-Token-Gen-Script
- Frontend-Backend Communication Documentation
- Backend Documentation (backend)
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driver.py - AWS Helper Files (backend.aws_helpers)
- Dynamo DB Utility Files (aws_helpers.dynamo_db_utils)
- AWS Secrets Utility Files (aws_secrets_utils)
- AWS Batch Utility Files (aws_batch_utils)
- Firebase Helper Files (backend.firebase_helpers)
- Common Files (backend.common)
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constants.py -
dataset.py -
default_datasets.py -
email_notifier.py -
loss_functions.py -
optimizer.py -
utils.py - Deep Learning Files (backend.dl)
- Machine Learning Files (backend.ml)
- Frontend Documentation
- Bug Manual
- Developer Runbook
- Examples to locally test DLP
- Knowledge Share