IEEE

Scalable and Generalizable Cross-Domain Invariant Network Analysis and Intrusion Detection System Using Deep Learning

Abstract: Modern networks are increasingly complex and diverse—especially with the rapid growth of the Internet of Things (IoT) and Industrial IoT (IIoT)—so intrusion detection (ID) models that are ...
GitHub

GitHub - kossisoroyce/timber: Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code ...

Timber takes a trained ML model — XGBoost, LightGBM, scikit-learn, CatBoost, ONNX (tree ensembles, linear models, SVMs, k-NN, Naive Bayes, GPR, Isolation Forest), or a URDF robot description — runs it ...
Frontiers

Machine learning methods for predicting human-adaptive influenza A virus reassortment based on intersegment constraint

It is not clear about mechanisms underlining the inter-segment reassortment of Influenza A viruses (IAVs).We analyzed the viral nucleotide composition (NC) in coding sequences,examined the ...
C&EN

Improved Machine Learning-Based Model for the Classification of Off-Targets in the CRISPR/Cpf1 System

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Article Views are the COUNTER-compliant sum of full text article downloads since ...
Visual Studio Magazine

Binary Classification Using a scikit Neural Network

Machine learning with neural networks is sometimes said to be part art and part science. Dr. James McCaffrey of Microsoft Research teaches both with a full-code, step-by-step tutorial. A binary ...
Hacker

Build a GUI for Your Machine Learning Models

Breaking down complex concepts for those with more than a passing interest in AI. Contact Me: edemgold@skiff.com If you have ever built a Machine Learning model, you've probably felt, well, this was ...
GitHub

pymc-learn: Practical Probabilistic Machine Learning in Python

pymc-learn is a library for practical probabilistic machine learning in Python. The difference between the two models is that pymc-learn estimates model parameters using Bayesian inference algorithms ...