Throughout this book, you've gained experiences that form the technical foundations for professional work in deep learning projects. However, the scope of the book was such that our focus could only be on a subset of the entire production-scale data science pipeline. We spent our time in the context of a business use case to ground our thinking on the domain and success criteria, but quickly dove into deep-learning model training, evaluation, and validation. These components, comprising the bulk of the training in our projects, are certainly the core of a data science pipeline for an enterprise, but cannot function in a vacuum. Additional considerations and training in AI strategy and data science platforms are the natural next steps in your education and career.
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