Implementation of KNN using PySpark. The KNN was used on two separate datasets (https://archive.ics.uci.edu/ml/datasets/iris and https://archive.ics.uci.edu/ml/datasets/Fertility). The data was first normalized, also using PySpark. Euclidean Distance was used as the similarity measure. The optimal k found for both datasets was 5. The iris dataset had a test accuracy of 97% and the fertility dataset had a test accuracy of 88%.
Stacking (stacked generalization) Overview ikki407/stacking - Simple and useful stacking library, written in Python. User can use models of scikit-lea
Quaternions in numpy This Python module adds a quaternion dtype to NumPy. The code was originally based on code by Martin Ling (which he wrote with he
A library for debugging/inspecting machine learning classifiers and explaining their predictions
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
Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera
Generator of Rad Names from Decent Paper Acronyms
adaptive Adaptive: parallel active learning of mathematical functions. adaptive is an open-source Python library designed to make adaptive parallel fu
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.
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
The code from the Machine Learning Bookcamp book and a free course based on the book
giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).
Simple Keyword Clusterer A simple machine learning package to cluster keywords in higher-level groups. Example: "Senior Frontend Engineer" -- "Fronte
Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp
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
**Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining.** S
Machine Learning Engineering for Production (MLOps) Specialization on Coursera (offered by deeplearning.ai) Programming assignments from all courses i
python-is-cool A gentle guide to the Python features that I didn't know existed or was too afraid to use. This will be updated as I learn more and bec
Bayesian Modeling and Computation in Python Open access and Code This repository contains the open access version of the text and the code examples in
This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment to test the algorithm
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