Testing ML systems
Practical AI
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Navigating Jupyter Notebooks in Machine Learning
This chapter explores the use of Jupyter Notebooks in machine learning, focusing on their benefits and the challenges they pose for reproducibility and system integrity. It underscores the need for structured workflows and the transition towards more robust software engineering practices as models mature. Additionally, the chapter offers insights into enhancing Python coding skills and recommends tools and resources for improving software development in data science.
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