Machine learning (ML) pipelines consist of several steps to train a model, but the term ‘pipeline’ is misleading as it implies a one-way flow of data. Instead, machine learning pipelines are cyclical and iterative as every step is repeated to continuously improve the accuracy of the model and achieve a successful algorithm.

To build better machine learning models, and get the most value from them, accessible, scalable and durable storage solutions are imperative, paving the way for on-premises object storage. Machine Learning Is Burgeoning Welcome to the era of digital transformation, where data has become a modern-day currency. Tremendous value and intelligence is being extracted from large, captured datasets (big data) that has led to actionable insights through today’s analytics.

Source: datanami.com
Author: Linda Zhou