How To Build an ML Platform from Scratch
As your data science team grows and you start deploying models to production, the need for proper ML infrastructure becomes...
Prompt engineering sucks. Break free from the endless tweaking with this revolutionary approach - Learn more
Securing AI systems is tricky, ignoring it is risky. Discover the easiest way to secure your AI end to end - Learn more
An ML Platform or machine learning platform is a module providing the user with a system that manages the modeling lifecycle, focusing on experimentation, reproducibility, and deployment.
During the research phase, a data scientist tests different hypotheses using a variety of features in order to achieve the best results. In order to manage experiments, data scientists can use an ML Platform for reusable components which can be inserted into any Python script and also provides specific interfaces for different frameworks like TensorFlow or Scikit-Learn
ML Platforms will implement faster insights and greater business impact if used by a team. They can optimize a company’s machine learning efforts by implementing MLOps and enhancing insights.