Data Preprocessing and Visualization

The ability to clean, preprocess, and visualize data is critical. Understanding how to handle missing values, normalize data, and use tools like Matplotlib and Seaborn for data visualization can uncover insights and improve model performance.

The ability to clean, preprocess, and visualize data is critical. Understanding how to handle missing values, normalize data, and use tools like Matplotlib and Seaborn for data visualization can uncover insights and improve model performance.

Empowered by Artificial Intelligence and the women in tech community.
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Rutika Bhoir
Grad Student at Umass Amherst

This is way more important than I thought! Along with models or fancy algorithms, you have to know how to clean and understand your data. Handling missing values, normalizing features, and just… making sense of messy real-world datasets is a skill. Tools like Pandas, Matplotlib, and Seaborn help a lot, and honestly, visualizing the data is where I often get my “aha” moments. So if you're just starting out, don’t skip this step. Great models start with good data. And you will get better the more you practice.

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