Lifecycle of a Data Science Project

Data science is now a crucial part of modern business, and at its core is the data scientist, an expert in data analysis, machine learning, and data-driven decision-making. The data scientist’s work follows a lifecycle that includes problem definition, data collection, data cleaning, analysis, feature engineering, feature selection, model training & evaluation, and model deployment. Data scientists can help businesses gain insights, identify trends, and develop predictive models that inform strategic decision-making and drive business success by following this process.

As data science plays a pivotal role in driving business growth and innovation, understanding this life cycle is essential for businesses looking to leverage data and gain a competitive edge. By following the steps outlined in this infographic, companies can successfully navigate the complexities of a data science project to achieve their desired outcome.

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