Data Science Lifecycle

In the wake of the public introduction of ChatGPT, the field of artificial intelligence is experiencing a remarkable surge. Complex and large-scale AI solutions are being unveiled at a rapid pace. However, amid this era of innovation, it’s essential to revisit the fundamentals.

In this white paper, our focus is on stripping away the complexity and taking a step back to examine the core building blocks of AI solutions. Regardless of the size or scope of the use case, the foundation of AI remains consistent. These fundamental steps collectively constitute what we refer to as the data science lifecycle.

By breaking down the process into its basic components, we aim to provide a clear and accessible framework for understanding the core of data science and AI.

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