SciKits (short for SciPy Toolkits) are add-on packages for SciPy, hosted and developed separately and independently from the main SciPy distribution. All SciKits are licensed under OSI-approved licenses.
Tensor Train Toolbox
Rating: (6/10) The project uses Python libraries and APIs to analyze Reddit data, predict user input, suggest new titles based on cosine similarity, calculate combined scores, and output the best suggestion.
A new maintained "successor" to scikit-multilearn, a scikit-learn based module for multi-label et. al. classification
Source for book "Feature Engineering A-Z"
Neural Tangent Kernel (NTK) module for the scikit-learn library
Collection of algorithms and routines for (ultrafast) electron diffraction and scattering
A parser for scikit-learn exported text models to execute in the Java runtime.
This project is to build a model that *predicts the human activities* such as __Walking, Walking_Upstairs, Walking_Downstairs, Sitting, Standing__ and __Laying__ as done in Smart-Watches.
An algorithmic cryptocurrency trading bot supported by Python TensorFlow Library
Customer Segmentation project utilizing the K-Means clustering algorithm
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Three projects as a freelance Data Scientist for USISA, largest canning company in Andalucia. Forecasting prediction of sales, recommendation system and clustering.
The main focus of this project is on analyzing and classifying handwritten digits (0-9) from the MNIST dataset. It includes: Statistical analysis of digit images Visualization of digit features Classification using logistic regression and support vector machines (SVM)
A scikit-learn based module for multi-label et. al. classification