M6 comptition files

Steps:

Run download.py to create a data dataframe -> data will have history and future (start and end dates of future should change)
Run feature_genearation.py to create history and future dataframes. An initial feature genration is added to simply shift the values over future horizon.
Run baseline.py to train and save models (CV = 3). It also reports bias and wmape on a test set.
Run create_submission_file

Name		Name	Last commit message	Last commit date
Latest commit History 22 Commits
models		models
old_submission_files		old_submission_files
Dockerfile		Dockerfile
M6_Universe.csv		M6_Universe.csv
README.md		README.md
assets_m6.csv		assets_m6.csv
baseline.py		baseline.py
create_submission_file.py		create_submission_file.py
docker-compose.yml		docker-compose.yml
download.py		download.py
feature_generation.py		feature_generation.py
first_submission.csv		first_submission.csv
full_asset_m6.csv		full_asset_m6.csv
full_asset_m6_future.csv		full_asset_m6_future.csv
full_asset_m6_history.csv		full_asset_m6_history.csv
pred.py		pred.py
requirements.txt		requirements.txt
submission.csv		submission.csv

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