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Logo of the Software Freedom Conservancy's Reproducible Builds project. Reproducible builds, also known as deterministic compilation, is a process of compiling software which ensures the resulting binary code can be reproduced.
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
In software engineering, a software development process or software development life cycle (SDLC) is a process of planning and managing software development. It typically involves dividing software development work into smaller, parallel, or sequential steps or sub-processes to improve design and/or product management .
Reproducibility: This allows for researchers to use the exact methods used to calculate the relations between biological data. Faster development: developers and researchers do not have to reinvent existing code for minor tasks. Instead they can use pre-existing programs to save time on the development and implementation of larger projects.
Model organisms each have some particular experimental advantages which have enabled them to become popular among researchers. In one sense they are "models" for the whole animal kingdom, and in another sense they are "models" for human development, which is difficult to study directly for both ethical and practical reasons.
MLOps or ML Ops is a paradigm that aims to deploy and maintain machine learning models in production reliably and efficiently. The word is a compound of "machine learning" and the continuous delivery practice (CI/CD) of DevOps in the software field. Machine learning models are tested and developed in isolated experimental systems.
As a whole, these models argue the inadequacy of the modern evolutionary synthesis on the roles of genes and natural selection as the principal explanation of living structures. Developmental systems theory embraces a large range of positions that expand biological explanations of organismal development and hold modern evolutionary theory as a ...
ModelOps is an evolution of MLOps that expands its principles to include not just the routine deployment of machine learning models but also the continuous retraining, automated updating, and synchronized development and deployment of more complex machine learning models. [14] ModelOps refers to the operationalization of all AI models ...