Edgar Bahilo Rodríguez's repositories
econ-dispatch
Work space for in development Economic Dispatch Application
Power-Market-Operations-Final-Project-Unit-Commitment
Security-Constrained Unit Commitment Programming Project
Ubiqum_Project.3
Energy Consumption Optimization - IoT
AE_ts
Auto encoder for time series
anomaly-detection-resources
Anomaly detection related books, papers, videos, and toolboxes
autoencoder_classifier
Autoencoder model for rare event classification
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
benchm-ml
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
ENAS-pytorch
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"
lstm_autoencoder_classifier
An LSTM Autoencoder for rare event classification
m2cgen
Transform ML models into a native code (Java, C, Python, Go) with zero dependencies
ma-thesis
Use RL to balance the electrical power grid with electric vehicle fleets
Machine-Learning
Some of the ML codes I have come across
Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
MEEKNESS
Multiple RDBMS and application project featuring meek fictional characters in literature, films, television, songs
mit-deep-learning
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
most
MOST – MATPOWER Optimal Scheduling Tool, for steady-state power systems scheduling problems.
ND-Pyomo-Cookbook
A repository of Pyomo examples.
Real-time-ML-Project
A curated list of applied machine learning and data science notebooks and libraries across different industries.
RNN-Time-series-Anomaly-Detection
RNN based Time-series Anomaly detector model implemented in Pytorch.
SDDP.jl
Stochastic Dual Dynamic Programming in Julia
STLDecompose
A Python implementation of Seasonal and Trend decomposition using Loess (STL) for time series data.
telemanom
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
TStrain
Approaches and methods for training forecasting models
tutorial-grid-science-2019
Julia Tutorial Materials for the Grid Science Winter School 2019
umap-explorer
An interactive UMAP visualization of the MNIST data set.
urbs
A linear optimisation model for distributed energy systems