Chad Delany's repositories
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
probabilistic_programming_language
Project work with PyMC and CausalPy.
python_coding_examples
a collection of python projects
ChadDelany
Config files for my GitHub profile.
ssm_book_club
State Space Models book club
causal_inference_castle_doctrine
A causal inference study using difference-in-differences techniques to study changes in gun laws and lethal violence.
causalpy_examples
Introductory examples of Bayesian Causal Inference using CausalPy.
drought_prediction
Modeling drought using rudimentary meteorological and soil variables. Used RAPIDS framework to access GPU processing for large datasets.
DataScienceGuidedCapstone
Project for Data Science certificate at Springboard
Case_Study-GridSearchKNN
This case study is all about using grid searches to identify the optimal parameters for a machine learning algorithm. To complere this case study, you'll use the Pima Indian diabetes dataset from Kaggle and KNN. Follow along with the preprocessing steps of this case study.
featuretools_exercise
Adapted exercise from here: https://github.com/Featuretools/predict-customer-churn/blob/master/churn/3.%20Feature%20Engineering.ipynb
Case_Study-Segmentation_using_Clustering
In this case study, you will implement the K-Means clustering algorithm, find the value for K using the Elbow method, the Silhouette method, and the Gap statistic, and visualize the clusters with Principal Components Analysis (PCA). You'll use real data containing information on marketing newsletters and email campaigns, as well as transaction-level data from customers.
Case_Study-Random_Forest
Use of Random Forest Model and Logistic Regression to study the Coronavirus
Case_Study-Linear_Regression
11.4 Springboard Case Study - Linear Regression
Apps_Case_Study
Integrating Apps Case Study
springboard_data_science
Collection of work from the Springboard Data Science program.