Bike-Rental-Demand-Forecasting-using-AWS-SageMaker

Conducted thorough statistical data analysis to identify key factors affecting bike rentals by implementing and deploying an XGBoost model, sourced from AWS Elastic Container Registry.

Ref: GreatLearning

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
.gitattributes		.gitattributes
1-biketrain-data_preparation.ipynb		1-biketrain-data_preparation.ipynb
2-biketrain-xgboost_training.ipynb		2-biketrain-xgboost_training.ipynb
3-biketrain-xgboost_prediction.ipynb		3-biketrain-xgboost_prediction.ipynb
LambdaFunction		LambdaFunction
README.md		README.md
bike_all.csv		bike_all.csv
bike_test.csv		bike_test.csv
bike_train.csv		bike_train.csv
bike_train_column_list.txt		bike_train_column_list.txt
bike_val.csv		bike_val.csv
model.tar.gz		model.tar.gz
predicted_count_cloud.csv		predicted_count_cloud.csv
sample_json_input_for_api		sample_json_input_for_api
test.csv		test.csv
train.csv		train.csv

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