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Exploring Sports Data using Data Analysis, Data Science and ML

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.github/workflows
.github/workflows
 
 
__pycache__
__pycache__
 
 
app
app
 
 
deploy
deploy
 
 
mock_data
mock_data
 
 
profiling
profiling
 
 
prototypes
prototypes
 
 
reports
reports
 
 
src
src
 
 
tests
tests
 
 
.DS_Store
.DS_Store
 
 
.gitignore
.gitignore
 
 
__init__.py
__init__.py
 
 
auth.sh
auth.sh
 
 
fpl
fpl
 
 
init_env.sh
init_env.sh
 
 
observations.md
observations.md
 
 
readme.md
readme.md
 
 
requirements.in
requirements.in
 
 
requirements.txt
requirements.txt
 
 
scrap_requirements.txt
scrap_requirements.txt
 
 
work_on.md
work_on.md
 
 

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Goal: Create an analytic tool for Fantasy Premier League

Web application ./app

Data scraping and gathering, Writing to DB

Feature prototyping

Analytic features

Tests

Containerisation

Resource provisioning and deployment .

Continuous integration and deployment workflows

Create APIs

Tools: Python, SQLite, Pandas, Django, Pytest, GCP, Terraform, pip

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Exploring Sports Data using Data Analysis, Data Science and ML

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