Skip to content
/ scalable-ML Public
forked from rajeevdixit19/Scaleable-Ml

In this repo, I build a LogisticRegression prediction model with Dask and PySpark and initialize an AWS EMR cluster to run the entire pipeline.

0 stars 1 fork Branches Tags Activity
Star
Notifications You must be signed in to change notification settings

arjunsawhney1/scalable-ML

BranchesTags
 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

19 Commits
README.md
README.md
 
 
dask_UI.png
dask_UI.png
 
 
ec2_initialization.sh
ec2_initialization.sh
 
 
emr_initialization.sh
emr_initialization.sh
 
 
feature_prep.py
feature_prep.py
 
 
final_model.py
final_model.py
 
 
label_prep.py
label_prep.py
 
 
model_requirements.txt
model_requirements.txt
 
 
requirements.txt
requirements.txt
 
 

Repository files navigation

Scaleable-Ml

This project predicts the deliquency rate in the Freddie Mac dataset in a distributed way using Dask and PySpark.

About

In this repo, I build a LogisticRegression prediction model with Dask and PySpark and initialize an AWS EMR cluster to run the entire pipeline.

Topics

aws spark aws-s3 scalability pyspark logistic-regression aws-ec2 dask aws-emr-clusters dask-ml dask-distributed

Resources

Readme
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

No releases published

Packages

No packages published

Languages

  • Python 94.5%
  • Shell 5.5%