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Overcoming Challenges in Building an AI-Driven Product
This chapter explores the obstacles faced in developing a product driven by AI and machine learning, including outdated and unsupported models, making experiments visible, managing and increasing data, structuring code, exchanging data, labeling data, and building a labeling tool. It also offers practical advice on getting started in AI and machine learning, such as using tools like Hugging Face and PyTorch Lightning, implementing a version control system for data, and fostering collaboration between machine learning researchers and software engineers.