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ace_592

appliedstats

:bar_chart: Methods of Applied Statistics Course Textbook Repository

awesome-network-analysis

A curated list of awesome network analysis resources.

caesar_cipher

My solution to the Caesar Cipher challenge using basic Python lists and functions.

credit_risk_modeling

data-science-and-machine-learning-bootcamp-with-r

Data Science and Machine Learning Bootcamp with R: https://www.udemy.com/course/data-science-and-machine-learning-bootcamp-with-r/learn/lecture/5413116#overview by Jose Portilla, Head of Data Science, Pierian Data Inc.

datasciencecoursera

Exercise for data science course using R

datasharing

The Leek group guide to data sharing

decisiontreeclassification_python

An end-to-end decision tree classification tutorial, with theory and code.

effective-pandas

Source code for my collection of articles on using pandas.

experimentdata

financepy

A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.

financial-analysis-projects-using-python

Developing trading strategies as machine learning classification: Feature engineering, k-nearest neighbors, decision trees & random forests, and strategic quant trading

garch-models-in-r

Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) models are good for times series data that are very volatile. This sample project showcases how various GARCH models can be fitted and how predictions can be made. Apple stock prices are used for the application.

hello-world

My first repository using R! I created this repository entirely using instructions at this location: https://guides.github.com/activities/hello-world/. Check it out!

home_value_modeling_sas

We use the Statistical Analysis Software (SAS/SAT) to model home sale price. Codes and outputs are included in the project.

hyperparameter-optimization

Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms

interpretable-ml-book

Book about interpretable machine learning

introduction-to-regression-with-statsmodels-in-python

Introduction to Regression with statsmodels in Python. A DataCamp tutorial.

machine-learning-capstone-project

Capstone project for completion of Udacity's Machine Learning Engineering Nano Degree.

machine-learning-projects

Machine Learning Experiments and Work

machine-learning-projects-using-python

Collection of 11 projects: Sales (2 projects), Marketing (3 projects), Operations (1 projects), Finance (2 projects), Customer Support (1 project), Human Resources (1 project), and Information Technology (1 project)

markov-chain

SAS Codes for Markov Chain

merger-and-acquisition-simulation

The purpose of this project is to simulate the process of merger and acquisition (i.e., M&A) between three firms and project their ex-post market valuation, as well as the resulting margin from the operation. Merger simulation models predict post-merger prices based on information about a set of pre-merger market conditions and certain assumptions about the behavior of the firms in the relevant market. This project replicates the analysis in the seminal M&A paper by Rubinfeld and Epstein (2001).

multi-output-regression-models

Multioutput regression are regression problems that involve predicting two or more numerical values given an input example. This tutorial covers how to develop models for multi-output regression.

predict_insurance_purchase

The purpose of this FUN project is to use machine learning to predict the probability that each customer would purchase an insurance product.

preprocess_lending_club_data

Pre-processes lending club loan data and concatenates into one large file.

promotionskollegmodule6800_2020

Course material and links for Promotionskolleg module "Machine learning in applied economics"

python-time-series

Simple Moving Averages, Exponential Weighted Moving Averages, ETS (Error, Trend & Seasonality) Decomposition, ARIMA, and SARIMAX

pyziabm

Zero Intelligence Agent-Based Model of Modern Limit Order Book