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For data collection, data scientists must know the tools for collecting data and preparing training data for machine learning, in addition to why data is crucial for ML algorithms.

ML models for Self-driving cars need to understand the context in the environment in which they’re operating. #SemanticSegmentation doing what it does best.

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A structured approach focusing on numerical data collection through predefined questions and visual representation for statistical analysis. An exploratory method centered on open-ended inquiries, aiming to gather rich, descriptive insights through discussions and thematic analysis.

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Use of net bags during sampling to prevent seed loss.

Collected samples for grain yield measurement

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