
Based on the “Machine Learning ” crash course from Google for Developers: https://developers.google.com/machine-learning/crash-course
Before feeding data into a machine learning model, it’s crucial to understand it. This episode walks you through the essential first steps: visualizing data, calculating basic statistics like mean and percentiles, and spotting outliers that could skew your model. Whether you're using pandas or plotting histograms, these techniques lay the foundation for effective ML pipelines.
Disclaimer: This podcast is generated using an AI avatar voice. At times, you may notice overlapping sentences or background noise. That said, all content is directly based on the official course material to ensure accuracy and alignment with the original learning experience.