Kim M Jarabin's repositories
dlt-meta
This is metadata driven DLT based framework for bronze/silver pipelines
EcpEmuServer
Trigger webhooks from your Logitech Harmony (or other Roku ECP compatible) Universal Remote
docker-airflow
Docker Airflow - Contains a docker compose file for Airflow 2.0
tickit-data-lake-demo
Resources for video demonstrations and blog posts related to DataOps on AWS
MLOps-IRIS
Create a fully automated, end-to-end IRIS Training and Deployment using Azure MLOps
nlpia
Examples and libraries for "Natural Language Processing in Action" book
machine-learning
Practical Full-Stack Machine Learning
xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
featuretools
An open source python library for automated feature engineering
py
Repository to store sample python programs for python learning
Getting-to-a-Hyperparameter-Tuned-XGBoost-Model-in-No-Time
Blog post Getting to a Hyperparameter-Tuned XGBoost Model in No Time: How to fine-tune your first XGBoost model in R with random search
FES
Code and Resources for "Feature Engineering and Selection: A Practical Approach for Predictive Models" by Kuhn and Johnson
customer_churn_analysis
In the customer management lifecycle, customer churn refers to a decision made by the customer about ending the business relationship. It is also referred as loss of clients or customers. Customer loyalty and customer churn always add up to 100%. If a firm has a 60% of loyalty rate, then their loss or churn rate of customers is 40%. As per 80/20 customer profitability rule, 20% of customers are generating 80% of revenue. So, it is very important to predict the users likely to churn from business relationship and the factors affecting the customer decisions. We are going to show how logistic regression model using R can be used to identify the customer churn in the telecom dataset.
statistics_with_python
Statistics and Probability with Python for Everyone
churn_prediction
Repo containing R code for donor churn prediction
iLab1
Everything related to the iLab1 project as part of MDSI at UTS
statistics_multi
Repo for the course Applied multivariate statistics
WhatsAppR
R Package with functions for importing and analysing WhatsApp chat histories
Python_UMich
Python for Everybody Specialization @ Coursera - Fall 2015/2016
predict410
Northwestern University PREDICT 410: Predictive Modeling I
courses
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
swirl_courses
A collection of interactive courses for the swirl R package.