A Python tools for deriving R-Type adaptors for Wave Digital Filters.
This code is not quite production-ready. If you are interested in contributing, please contact me through this repository.
In order to use this script, you must have the Sage software system installed. From there, you can run the r_solver.py script to generate a scattering matrix for a given netlist. For more options, use r_solver.py --help.
time-series This package contains all necessary files for the course Ocean/Atmosphere Time Series Analysis, an introduction to data and time series an
Linear_Regression_Model A linear regression model for house price prediction. This code is using these packages, so please make sure your have install
ETNA is an easy-to-use time series forecasting framework. It includes built in toolkits for time series preprocessing, feature generation, a variety of predictive models with unified interface - from
Organic Alkalinity Sausage Machine A Python toolbox to churn out organic alkalinity calculations with minimal brain engagement. Getting started To mak
This is a TensorFlow implementation of an arbitrary order (=2) Factorization Machine based on paper Factorization Machines with libFM. It supports: d
The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machine Learning Experiment (MLE) pipeline.
sk-dist: Distributed scikit-learn meta-estimators in PySpark What is it? sk-dist is a Python package for machine learning built on top of scikit-learn
vortex-particles-method-2d vortex particles for simulating smoke in 2d -vortexparticles_s
What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss
Cryptocurrency price prediction and exceptions in python This is a coursework on foundations of computing module Through this coursework i worked on m
Parallelized symbolic regression built on Julia, and interfaced by Python. Uses regularized evolution, simulated annealing, and gradient-free optimization.
giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G
Nevergrad - A gradient-free optimization platform nevergrad is a Python 3.6+ library. It can be installed with: pip install nevergrad More installati
FEATURE ENGINEERING Business Problem: A data preprocessing and feature engineering script for a machine learning pipeline needs to be prepared. It is
06.demand-electricity Predict the demand for electricity (R) - FRENCH Prédisez la demande en électricité Prérequis Pour effectuer ce projet, vous devr
2021 Machine Learning Security Evasion Competition This repository contains code samples for the 2021 Machine Learning Security Evasion Competition. P
Suiron Machine Learning for RC Cars Prediction visualization (green = actual, blue = prediction) Click the video below to see it in action! Dependenci
It selects the best indexing parameters to achieve the highest recalls given memory and query speed constraints.
Getting Profit and Loss Make Easy From Binance I have been in Binance Automated Trading for some time and have generated a lot of transaction records,
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed
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