Showing 281 - 286 results of 286 for search '((python model) OR (python code)) implemented', query time: 0.19s Refine Results
  1. 281

    Soulware-Lite by Abhiram Gnyanijaya (21572942)

    Published 2025
    “…It supports OpenAI GPT-4, Anthropic Claude, Google Gemini, Meta LLaMA, and other open-source models.</p><p><br></p><p dir="ltr">Soulware-Lite is the first live implementation of a cognitive conscience layer, born from architectural failures in AI output hallucination and anchored by integrity principles like MAP/ARP and RDIP. …”
  2. 282

    Gene Editing using Transformer Architecture by Rishabh Garg (5261744)

    Published 2025
    “…., the H-Bot sequence), it facilitates on-screen gene editing, enabling targeted mutations or the insertion of desired genes. Implementation requires Python and deep learning frameworks like TensorFlow or PyTorch, with optional use of Biopython for genetic sequence handling. …”
  3. 283

    Globus Compute: Federated FaaS for Integrated Research Solutions by eRNZ Admin (6438486)

    Published 2025
    “…</p><p dir="ltr">Globus Compute [2] is a Function-as-a-Service platform designed to provide a scalable, secure, and simple interface to HPC resources. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, from the edge to high performance computing (HPC) cluster, and they may then invoke Python functions on those endpoints via a reliable cloud-hosted service. …”
  4. 284

    OHID-FF dataset for forest fire detection and classification by xin chen (20496938)

    Published 2025
    “…</p><p dir="ltr">- Pointed to the `train val scripts/` README for model-specific commands and dependencies.</p>…”
  5. 285

    Mean Annual Habitat Quality and Its Driving Variables in China (1990–2018) by ChenXi Zhu (21374876)

    Published 2025
    “…</p><p dir="ltr">(HQ: Habitat Quality; CZ: Climate Zone; FFI: Forest Fragmentation Index; GPP: Gross Primary Productivity; Light: Nighttime Lights; PRE: Mean Annual Precipitation Sum; ASP: Aspect; RAD: Solar Radiation; SLOPE: Slope; TEMP: Mean Annual Temperature; SM: Soil Moisture)</p><p dir="ltr"><br>A Python script used for modeling habitat quality, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), and implementation of four machine learning models to predict habitat quality.…”
  6. 286

    Landscape Change Monitoring System (LCMS) Conterminous United States Cause of Change (Image Service) by U.S. Forest Service (17476914)

    Published 2025
    “…Scikit-learn: Machine Learning in Python. In Journal of Machine Learning Research (Vol. 12, pp. 2825-2830).Pengra, B. …”