Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them.
Reproducible Experiment Platform (REP) REP is ipython-based environment for conducting data-driven research in a consistent and reproducible way. Main
By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated
QML is a Python2/3-compatible toolkit for representation learning of properties of molecules and solids.
Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L
About scikit-learn is a python module for machine learning built on top of numpy / scipy. The purpose of the scikit-learn-tutorial subproject is to le
The Machine Learning package simply contains sample datasets at present. It has some classification algorithms such as QSVM and VQC (Variational Quantum Classifier), where this data can be used for e
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se
Bayesian optimization in JAX
Python implementation of Weng-Lin Bayesian ranking, a better, license-free alternative to TrueSkill This is a port of the amazing openskill.js package
monolish is a linear equation solver library that monolithically fuses variable data type, matrix structures, matrix data format, vendor specific data transfer APIs, and vendor specific numerical alg
END TO END MACHINE LEARNING PROJECT ON HITTERS DATASET Can a machine learning project be implemented to estimate the salaries of baseball players whos
Price-Predictor Ml based project which uses regression technique to predict the price. I have used various regression models and finds the model with
Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera
Factorization Machines in Python This is a python implementation of Factorization Machines [1]. This uses stochastic gradient descent with adaptive re
AutoXGB XGBoost + Optuna: no brainer auto train xgboost directly from CSV files auto tune xgboost using optuna auto serve best xgboot model using fast
AutoTabular AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just
PLUR (Programming-Language Understanding and Repair) is a collection of source code datasets suitable for graph-based machine learning. We provide scripts for downloading, processing, and loading the
Hackerank-Nested-List Given the names and grades for each student in a class N of students, store them in a nested list and print the name(s) of any s
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
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