jesservillines
I am a data scientist with a passion for discovering and explaining the stories hidden in data.
Pinned Repositories
Data-Science-Resources
Data Science related resources and cheatsheets
Wildfire_Classifier
80x improvement from baseline on predicting wildfire size using geospatial and climate data. Multiple techniques applied for optimizing results including clustering, bootstrapping, time series analysis, class weighting and principal component analysis
BayesianOptimization
A Python implementation of global optimization with gaussian processes.
BioWordVec
Causal-Inference-and-Discovery-in-Python
Causal Inference and Discovery in Python by Packt Publishing
clinical-outcome-prediction
Code for the EACL 2021 Paper: Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration
clinicalBERT
ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission (CHIL 2020 Workshop)
Colorado_Avalanche_Maps
This repository will contain choropleth maps of avalanches by county and year starting with the state of Colorado.
CommonDataModel
Definition and DDLs for the OMOP Common Data Model (CDM)
Counting-from-Sky-A-Large-scale-Dataset-for-Remote-Sensing-Object-Counting-and-A-Benchmark-Method
Pytorch code for the paper Counting from Sky: A Large-scale Dataset for Remote Sensing Object Counting and A Benchmark Method
jesservillines's Repositories
jesservillines/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
jesservillines/Causal-Inference-and-Discovery-in-Python
Causal Inference and Discovery in Python by Packt Publishing
jesservillines/scipy2023-deeplearning
jesservillines/scipy_2023_causal_inference_tutorial
Materials for a proposed Causal Inference Tutorial session at SciPy 2023
jesservillines/scipy-2023-keras
jesservillines/CommonDataModel
Definition and DDLs for the OMOP Common Data Model (CDM)
jesservillines/raspberry-pi-dramble
DEPRECATED - Raspberry Pi Kubernetes cluster that runs HA/HP Drupal 8
jesservillines/openai-cookbook
Examples and guides for using the OpenAI API
jesservillines/deep-learning-and-rare-event-prediction
Deep Learning and Rare Event Prediction
jesservillines/poppy-humanoid
Poppy Humanoid is an open-source and 3D printed humanoid robot. Optimized for research and education purposes, its modularity allows for a wide range of applications and experimentations.
jesservillines/shap
A game theoretic approach to explain the output of any machine learning model.
jesservillines/clinical-outcome-prediction
Code for the EACL 2021 Paper: Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration
jesservillines/clinicalBERT
ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission (CHIL 2020 Workshop)
jesservillines/Wildfire_Classifier
80x improvement from baseline on predicting wildfire size using geospatial and climate data. Multiple techniques applied for optimizing results including clustering, bootstrapping, time series analysis, class weighting and principal component analysis
jesservillines/Text-Classification-with-SciBERT
Task of classifying scientific paper titles according the journal they were published in.
jesservillines/plant_classifier
jesservillines/Housing-Prices
Predict the housing price correctly within 91% of the actual price. Engineered model features specific to application needs and statistical significance. Normalized and regularized data and optimized hyperparameters to choose the best regression model for the case use. This Repository has a five-part walk-through that can be accessed starting here: https://jesservillines.medium.com/a-thorough-dive-into-the-ames-iowa-housing-dataset-part-1-of-5-7205093a5a53.
jesservillines/Introduction_to_Exploratory_Data_Analysis
jesservillines/Subreddit_nlp_pushshiftapi
jesservillines/propensity-score-matching
jesservillines/Colorado_Avalanche_Maps
This repository will contain choropleth maps of avalanches by county and year starting with the state of Colorado.
jesservillines/nasa_hls_tutorial
jesservillines/jobmatch
jesservillines/BayesianOptimization
A Python implementation of global optimization with gaussian processes.
jesservillines/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
jesservillines/LSTM-Neural-Network-for-Time-Series-Prediction
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
jesservillines/Data-Science-Resources
Data Science related resources and cheatsheets
jesservillines/stock-trading-ml
A stock trading bot that uses machine learning to make price predictions.
jesservillines/Counting-from-Sky-A-Large-scale-Dataset-for-Remote-Sensing-Object-Counting-and-A-Benchmark-Method
Pytorch code for the paper Counting from Sky: A Large-scale Dataset for Remote Sensing Object Counting and A Benchmark Method
jesservillines/BioWordVec