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In order to successfully implement a machine learning project, it is essential to establish a clear business case and identify the necessary data for model training. This includes considering the quantity, quality, and types of data needed, as well as how the model will operate on real-world data once deployed. Additionally, it is important to determine whether the model will be trained once or in iterations, and if it will be used in real-time.