A high-level machine learning and deep learning library for the PHP language.
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Updated
Nov 9, 2024 - PHP
A high-level machine learning and deep learning library for the PHP language.
scikit-learn cross validators for iterative stratification of multilabel data
Machine learning for C# .Net
Time Series Cross-Validation -- an extension for scikit-learn
Machine Learning with the NSL-KDD dataset for Network Intrusion Detection
It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization
State-of-the art Automated Machine Learning python library for Tabular Data
A Portfolio of my Data Science Projects
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
Automated rejection and repair of bad trials/sensors in M/EEG
The blockCV package creates spatially or environmentally separated training and testing folds for cross-validation to provide a robust error estimation in spatially structured environments. See
The implementation of 3D-UNet using PyTorch
Easy and comprehensive assessment of predictive power, with support for neuroimaging features
Hyperparameter tuning for machine learning models using a distributed genetic algorithm
LIBSVM for the browser and nodejs 🔥
Spatial Modelling for Data Scientists
🦅Hyperparameter optimization for machine learning pipelines 🦅
✋🏼🛑 This one stop project is a complete COVID-19 detection package comprising of 3 tasks: • Task 1 --> COVID-19 Classification • Task 2 --> COVID-19 Infection Segmentation • Task 3 --> Lung Segmentation
Customers in the telecom industry can choose from a variety of service providers and actively switch from one to the next. With the help of ML classification algorithms, we are going to predict the Churn.
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