Demystifying the Data Science Project Life Cycle

Navigating the journey from Data to Insights       In today's data-driven world, data science plays a crucial role in helping organizations to extract valuable insights and make informed decisions. Whether you're a data scientist, a business analyst, or simply curious about the field, understanding the data science project life cycle is essential. In this blogpost, we'll take a deep dive into the stages and steps that contribute the data science project life cycle. Step 1: Problem Definition   Step 2: Data Collection Step 3: Exploratory Data Analysis(EDA)  Step 4: Feature Engineering  Step 5: Model Selection  Step 6: Model Training  Step 7: Model Evaluation  Step 8: Model Testing Step 9: Model Deployment  Step 10: Feedback Loop Step 1: Problem Definition             Every data science project begins with a clear understanding of the problem you aim to solve. It's crucial to define the problem ...