Name: Dylan Loader
Type: User
Bio: MSc. Statistics Student at University of Calgary
If my code has errors or something isn't referenced properly, please tell me, always looking to improve.
Location: Edmonton, Alberta
Dylan Loader's Projects
A GLM analysis of Toronto AirBNB host ratings
The AMLSim project is intended to provide a multi-agent based simulator that generates synthetic banking transaction data together with a set of known money laundering patterns - mainly for the purpose of testing machine learning models and graph algorithms. We welcome you to enhance this effort since the data set related to money laundering is critical to advance detection capabilities of money laundering activities.
An assortment of random standalone projects of various types
Course material for MDSC401
A repo for holding example code
Some tools in R to work with BP energy data
A presentation template for CalgaryR speakers
Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.
Simulation code for my Biometrika paper "Analysis of grouped data using conjugate generalized linear mixed models"
A workspace for my work in copula modelling with R
The 3rd edition of course.fast.ai
A repo for learning NLP to generate cover letters.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
A repo for generating materials related to my job search
A project on green infrastructure monitoring as part of the M2PI workshop offered through PIMS
Data analysis tools for Math 2 Power Industry workshop By George Lee @Uvic
Free MLOps course from DataTalks.Club
Jupyter notebooks for the Natural Language Processing with Transformers book
Financial Simulator of Mobile Money Service
Fork of https://github.com/EdgarLopezPhD/PaySim
pysster: Learning Sequence And Structure Motifs In Biological Sequences Using Convolutional Neural Networks