#71 Scaling Machine Learning Adoption: A Pragmatic Approach
DataFramed
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Bridging Theory and Practice in Data Science
This chapter emphasizes the vital need for a pragmatic approach in data science and machine learning to address pressing global challenges. It highlights the transition from academic training to real-world applications, advocating for hands-on experience and industry-informed education. The discussion also covers effective communication of data solutions to stakeholders and the incorporation of automation tools to improve project alignment and efficiency.
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