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Clipper start install#
You can either install Clipper directly from GitHub:ġ7-08-30:15:59:56 INFO Anaconda environment found. Start a Clipper Instance and Deploy a Model This quickstart requires Docker and supports Python 2.7, 3.5, 3.6 and 3.7. For a quickstart that works with the released version of Clipper available on PyPi, go to our website Note: This quickstart works for the latest version of code. Clipper makes the infra-team less unhappy.Ĭlipper improves prediction accuracy by introducing state-of-the-art bandit and ensemble methods to intelligently select and combine predictions and achieve real-time personalization across machine learning frameworks. Clipper makes data scientists happy.Ĭlipper improves throughput and ensures reliable millisecond latencies by introducing adaptive batching, caching, and straggler mitigation techniques. Clipper makes product teams happy.Ĭlipper simplifies model deployment and helps reduce common bugs by using the same tools and libraries used in model development to render live predictions. What does Clipper do?Ĭlipper simplifies integration of machine learning techniques into user facing applications by providing a simple standard REST interface for prediction and feedback across a wide range of commonly used machine learning frameworks. Learn more about Clipper and view documentation at our website. What is Clipper?Ĭlipper is a prediction serving system that sits between user-facing applications and a wide range of commonly used machine learning models and frameworks. Note: Clipper is not actively maintained currently.
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