Description
Imagine a world where a whisper is as loud as a shout, where an inch is as long as a mile. That’s what it’s like for some AI models when features have vastly different scales. This imbalance can throw off their learning process, making some features seem more important than others.
Here are the essential techniques of feature scaling and normalization, the processes of adjusting the range and distribution of your data. Plus, an overview on how these methods can improve model accuracy, speed up training, and ensure fairness across all features. Get ready to fine-tune your AI’s senses and unleash its full potential.
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