Showing 3 open source projects for "genetic algorithm software"

View related business solutions
  • Gemini 3 and 200+ AI Models on One Platform Icon
    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

    Build generative AI apps with Vertex AI. Switch between models without switching platforms.
    Start Free
  • 8 Monitoring Tools in One APM. Install in 5 Minutes. Icon
    8 Monitoring Tools in One APM. Install in 5 Minutes.

    Errors, performance, logs, uptime, hosts, anomalies, dashboards, and check-ins. One interface.

    AppSignal works out of the box for Ruby, Elixir, Node.js, Python, and more. 30-day free trial, no credit card required.
    Start Free
  • 1
    X's Recommendation Algorithm

    X's Recommendation Algorithm

    Source code for the X Recommendation Algorithm

    The Algorithm is Twitter’s open source release of the core ranking system that powers the platform’s home timeline. It provides transparency into how tweets are selected, prioritized, and surfaced to users, reflecting Twitter’s move toward openness in recommendation algorithms. The repository contains the recommendation pipeline, which incorporates signals such as engagement, relevance, and content features, and demonstrates how they combine to form ranked outputs. Written primarily in...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 2
    TextTeaser

    TextTeaser

    TextTeaser is an automatic summarization algorithm

    textteaser is an automatic text summarization algorithm implemented in Python. It extracts the most important sentences from an article to generate concise summaries that retain the core meaning of the original text. The algorithm uses features such as sentence length, keyword frequency, and position within the document to determine which sentences are most relevant. By combining these features with a simple scoring mechanism, it produces summaries that are both readable and informative....
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    node2vec

    node2vec

    Learn continuous vector embeddings for nodes in a graph using biased R

    The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction....
    Downloads: 2 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB