Navigating the Machine Learning Lifecycle: Challenges and Solutions
Machine learning projects face distinct challenges compared to traditional software development. The iterative nature of model development, the reliance on high-quality data, and the need for continuous monitoring and retraining are just a few of the complexities involved. MLOps, a set of practices and tools designed to manage the entire machine learning lifecycle, addresses these …
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