Faced with a movie recommendation problem and want to create an endpoint to predict ratings based on prediction? Deploying machine learning models should not be harder than training them. That is why BentoML, an open-source framework is built to simplify model serving. It supports all major machine learning libraries and lets you package your model into a standardized service with APIs, containerization, and even autoscaling on Kubernetes.
From model to microservice in minutes, no DevOps headache required. Irrespective of your working with PyTorch, TensorFlow, XGBoost, or even custom models- BentoML wraps your model into a standard, containerized service that can be deployed via even serverless platforms such as AWS Lambda.
If you are someone who plans to enter the world of machine learning, mastering the recent advances in ML is a must. Grab top-notch AI-ML skills in leveraging large language models (LLMs), shall bring up an impactful long term data science career.
This exploration is a sheer take on the recent BentoML advances, what it means for the greater good of the data science industry.
Earn the latest proficiencies in machine learning to facilitate your role as a data scientist. Explore BentoML in details now!
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